def test_archiving_participations_does_not_change_results(self):
distribution = calculate_average_distribution(self.evaluation)
self.semester.archive_participations()
self.refresh_evaluation()
caches['results'].clear()
new_distribution = calculate_average_distribution(self.evaluation)
self.assertEqual(new_distribution, distribution)
def test_archiving_does_not_change_results(self):
distribution = calculate_average_distribution(self.course)
self.semester.archive()
self.refresh_course()
caches['results'].clear()
new_distribution = calculate_average_distribution(self.course)
self.assertEqual(new_distribution, distribution)
def test_average_grade(self):
question_grade2 = mommy.make(Question, questionnaire=self.questionnaire, type=Question.GRADE)
mommy.make(RatingAnswerCounter, question=self.question_grade, contribution=self.contribution1, answer=2, count=1)
mommy.make(RatingAnswerCounter, question=self.question_grade, contribution=self.contribution2, answer=4, count=2)
mommy.make(RatingAnswerCounter, question=question_grade2, contribution=self.contribution1, answer=1, count=1)
mommy.make(RatingAnswerCounter, question=self.question_likert, contribution=self.contribution1, answer=3, count=4)
mommy.make(RatingAnswerCounter, question=self.question_likert, contribution=self.general_contribution, answer=5, count=5)
mommy.make(RatingAnswerCounter, question=self.question_likert_2, contribution=self.general_contribution, answer=3, count=3)
mommy.make(RatingAnswerCounter, question=self.question_bipolar, contribution=self.general_contribution, answer=3, count=2)
mommy.make(RatingAnswerCounter, question=self.question_bipolar_2, contribution=self.general_contribution, answer=-1, count=4)
contributor_weights_sum = settings.CONTRIBUTOR_GRADE_QUESTIONS_WEIGHT + settings.CONTRIBUTOR_NON_GRADE_RATING_QUESTIONS_WEIGHT
contributor1_average = ((settings.CONTRIBUTOR_GRADE_QUESTIONS_WEIGHT * ((2 * 1) + (1 * 1)) / (1 + 1)) + (settings.CONTRIBUTOR_NON_GRADE_RATING_QUESTIONS_WEIGHT * 3)) / contributor_weights_sum # 2.4
contributor2_average = 4
contributors_average = ((4 * contributor1_average) + (2 * contributor2_average)) / (4 + 2) # 2.9333333
general_non_grade_average = ((5 * 5) + (3 * 3) + (2 * 5) + (4 * 7 / 3)) / (5 + 3 + 2 + 4) # 3.80952380
contributors_percentage = settings.CONTRIBUTIONS_WEIGHT / (settings.CONTRIBUTIONS_WEIGHT + settings.GENERAL_NON_GRADE_QUESTIONS_WEIGHT) # 0.375
general_non_grade_percentage = settings.GENERAL_NON_GRADE_QUESTIONS_WEIGHT / (settings.CONTRIBUTIONS_WEIGHT + settings.GENERAL_NON_GRADE_QUESTIONS_WEIGHT) # 0.625
total_grade = contributors_percentage * contributors_average + general_non_grade_percentage * general_non_grade_average # 1.1 + 2.38095238 = 3.48095238
average_grade = distribution_to_grade(calculate_average_distribution(self.evaluation))
self.assertAlmostEqual(average_grade, total_grade)
self.assertAlmostEqual(average_grade, 3.48095238)
def test_result_calculation_with_no_contributor_rating_question(self):
evaluation = baker.make(
Evaluation,
state=Evaluation.State.PUBLISHED,
participants=[self.student1, self.student2],
voters=[self.student1, self.student2],
)
questionnaire_text = baker.make(Questionnaire)
baker.make(Question,
questionnaire=questionnaire_text,
type=Question.TEXT)
baker.make(
Contribution,
contributor=baker.make(UserProfile),
evaluation=evaluation,
questionnaires=[questionnaire_text],
)
evaluation.general_contribution.questionnaires.set(
[self.questionnaire])
make_rating_answer_counters(self.question_grade,
evaluation.general_contribution,
[1, 0, 0, 0, 0])
cache_results(evaluation)
distribution = calculate_average_distribution(evaluation)
self.assertEqual(distribution[0], 1)
def get_evaluations_with_prefetched_data(evaluations):
if isinstance(evaluations, QuerySet):
participant_counts = evaluations.annotate(
num_participants=Count("participants")).values_list(
"num_participants", flat=True)
voter_counts = evaluations.annotate(
num_voters=Count("voters")).values_list("num_voters", flat=True)
course_evaluations_counts = evaluations.annotate(
num_course_evaluations=Count("course__evaluations")).values_list(
"num_course_evaluations", flat=True)
evaluations = (
evaluations.select_related("course__type").prefetch_related(
"course__degrees",
"course__semester",
"course__responsibles",
))
for evaluation, participant_count, voter_count, course_evaluations_count in zip(
evaluations, participant_counts, voter_counts,
course_evaluations_counts):
if evaluation._participant_count is None:
evaluation.num_participants = participant_count
evaluation.num_voters = voter_count
evaluation.course_evaluations_count = course_evaluations_count
for evaluation in evaluations:
if not evaluation.is_single_result:
evaluation.distribution = calculate_average_distribution(
evaluation)
evaluation.avg_grade = distribution_to_grade(
evaluation.distribution)
else:
evaluation.single_result_rating_result = get_single_result_rating_result(
evaluation)
return evaluations
def index(request):
user = request.user
contributor_visible_states = ['prepared', 'editor_approved', 'approved', 'in_evaluation', 'evaluated', 'reviewed', 'published']
own_courses = Course.objects.filter(contributions__contributor=user, state__in=contributor_visible_states)
represented_users = user.represented_users.all()
delegated_courses = Course.objects.exclude(id__in=own_courses).filter(contributions__can_edit=True, contributions__contributor__in=represented_users, state__in=contributor_visible_states)
all_courses = list(own_courses) + list(delegated_courses)
all_courses.sort(key=lambda course: list(STATES_ORDERED.keys()).index(course.state))
for course in all_courses:
course.distribution = calculate_average_distribution(course)
course.avg_grade = distribution_to_grade(course.distribution)
semesters = Semester.objects.all()
semester_list = [dict(
semester_name=semester.name,
id=semester.id,
is_active_semester=semester.is_active_semester,
courses=[course for course in all_courses if course.semester_id == semester.id]
) for semester in semesters]
template_data = dict(semester_list=semester_list, delegated_courses=delegated_courses)
return render(request, "contributor_index.html", template_data)
def test_get_single_result_rating_result(self):
single_result_course = mommy.make(Course,
state='published',
is_single_result=True)
questionnaire = Questionnaire.objects.get(
name_en=Questionnaire.SINGLE_RESULT_QUESTIONNAIRE_NAME)
contribution = mommy.make(Contribution,
contributor=mommy.make(UserProfile),
course=single_result_course,
questionnaires=[questionnaire],
responsible=True,
can_edit=True,
comment_visibility=Contribution.ALL_COMMENTS)
mommy.make(RatingAnswerCounter,
question=questionnaire.questions.first(),
contribution=contribution,
answer=1,
count=1)
mommy.make(RatingAnswerCounter,
question=questionnaire.questions.first(),
contribution=contribution,
answer=4,
count=1)
distribution = calculate_average_distribution(single_result_course)
self.assertEqual(distribution, (0.5, 0, 0, 0.5, 0))
rating_result = get_single_result_rating_result(single_result_course)
self.assertEqual(rating_result.counts, (1, 0, 0, 1, 0))
def get_evaluations_with_prefetched_data(evaluations):
if isinstance(evaluations, QuerySet):
participant_counts = evaluations.annotate(num_participants=Count("participants")).values_list("num_participants", flat=True)
voter_counts = evaluations.annotate(num_voters=Count("voters")).values_list("num_voters", flat=True)
course_evaluations_counts = evaluations.annotate(num_course_evaluations=Count("course__evaluations")).values_list("num_course_evaluations", flat=True)
evaluations = (evaluations
.select_related("course__type")
.prefetch_related(
"course__degrees",
"course__semester",
"course__responsibles",
)
)
for evaluation, participant_count, voter_count, course_evaluations_count in zip(evaluations, participant_counts, voter_counts, course_evaluations_counts):
if evaluation._participant_count is None:
evaluation.num_participants = participant_count
evaluation.num_voters = voter_count
evaluation.course_evaluations_count = course_evaluations_count
for evaluation in evaluations:
if not evaluation.is_single_result:
evaluation.distribution = calculate_average_distribution(evaluation)
evaluation.avg_grade = distribution_to_grade(evaluation.distribution)
else:
evaluation.single_result_rating_result = get_single_result_rating_result(evaluation)
return evaluations
def test_get_single_result_rating_result(self):
single_result_evaluation = baker.make(Evaluation,
state='published',
is_single_result=True)
questionnaire = Questionnaire.objects.get(
name_en=Questionnaire.SINGLE_RESULT_QUESTIONNAIRE_NAME)
contribution = baker.make(
Contribution,
contributor=baker.make(UserProfile),
evaluation=single_result_evaluation,
questionnaires=[questionnaire],
can_edit=True,
textanswer_visibility=Contribution.GENERAL_TEXTANSWERS)
baker.make(RatingAnswerCounter,
question=questionnaire.questions.first(),
contribution=contribution,
answer=1,
count=1)
baker.make(RatingAnswerCounter,
question=questionnaire.questions.first(),
contribution=contribution,
answer=4,
count=1)
distribution = calculate_average_distribution(single_result_evaluation)
self.assertEqual(distribution, (0.5, 0, 0, 0.5, 0))
rating_result = get_single_result_rating_result(
single_result_evaluation)
self.assertEqual(rating_result.counts, (1, 0, 0, 1, 0))
def get_evaluations_of_course(course, request):
course_evaluations = []
if course.evaluations.count() > 1:
course_evaluations = [
evaluation
for evaluation in course.evaluations.filter(state="published")
if evaluation.can_be_seen_by(request.user)
]
if request.user.is_reviewer:
course_evaluations += course.evaluations.filter(
state__in=['in_evaluation', 'evaluated', 'reviewed'])
course_evaluations = get_evaluations_with_course_result_attributes(
course_evaluations)
for course_evaluation in course_evaluations:
if course_evaluation.is_single_result:
course_evaluation.single_result_rating_result = get_single_result_rating_result(
course_evaluation)
else:
course_evaluation.distribution = calculate_average_distribution(
course_evaluation)
course_evaluation.avg_grade = distribution_to_grade(
course_evaluation.distribution)
return course_evaluations
def get_courses_with_prefetched_data(courses):
if isinstance(courses, QuerySet):
participant_counts = courses.annotate(
num_participants=Count("participants")).values_list(
"num_participants", flat=True)
voter_counts = courses.annotate(
num_voters=Count("voters")).values_list("num_voters", flat=True)
courses = (courses.select_related("type").prefetch_related(
"degrees", "semester",
Prefetch("contributions",
queryset=Contribution.objects.filter(
responsible=True).select_related("contributor"),
to_attr="responsible_contributions")))
for course, participant_count, voter_count in zip(
courses, participant_counts, voter_counts):
if course._participant_count is None:
course.num_participants = participant_count
course.num_voters = voter_count
course.responsible_contributors = [
contribution.contributor
for contribution in course.responsible_contributions
]
for course in courses:
if not course.is_single_result:
course.distribution = calculate_average_distribution(course)
course.avg_grade = distribution_to_grade(course.distribution)
else:
course.single_result_rating_result = get_single_result_rating_result(
course)
return courses
def test_result_calculation_with_no_contributor_rating_question_does_not_fail(
self):
evaluation = mommy.make(Evaluation,
state='published',
participants=[self.student1, self.student2],
voters=[self.student1, self.student2])
questionnaire_text = mommy.make(Questionnaire)
mommy.make(Question,
questionnaire=questionnaire_text,
type=Question.TEXT)
mommy.make(Contribution,
contributor=mommy.make(UserProfile),
evaluation=evaluation,
questionnaires=[questionnaire_text])
evaluation.general_contribution.questionnaires.set(
[self.questionnaire])
mommy.make(RatingAnswerCounter,
question=self.question_grade,
contribution=evaluation.general_contribution,
answer=1,
count=1)
distribution = calculate_average_distribution(evaluation)
self.assertEqual(distribution[0], 1)
def index(request):
# retrieve all courses which have evaluations that are not in state "new" and in which the user participates
courses = Course.objects.filter(
evaluations__participants=request.user,
evaluations__state__in=['prepared', 'editor_approved', 'approved', 'in_evaluation', 'evaluated', 'reviewed', 'published']
).distinct()
# retrieve all evaluations which the user can see that are not new
evaluations = [evaluation for course in courses for evaluation in course.evaluations.all() if evaluation.can_be_seen_by(request.user)]
for evaluation in evaluations:
if evaluation.state == "published":
if not evaluation.is_single_result:
evaluation.distribution = calculate_average_distribution(evaluation)
evaluation.avg_grade = distribution_to_grade(evaluation.distribution)
else:
evaluation.single_result_rating_result = get_single_result_rating_result(evaluation)
evaluation.participates_in = request.user in evaluation.participants.all()
evaluation.voted_for = request.user in evaluation.voters.all()
evaluations = get_evaluations_with_course_result_attributes(evaluations)
evaluations.sort(key=lambda evaluation: evaluation.full_name) # evaluations must be sorted for regrouping them in the template
semesters = Semester.objects.all()
semester_list = [dict(
semester_name=semester.name,
id=semester.id,
is_active_semester=semester.is_active_semester,
results_are_archived=semester.results_are_archived,
grade_documents_are_deleted=semester.grade_documents_are_deleted,
evaluations=[evaluation for evaluation in evaluations if evaluation.course.semester_id == semester.id]
) for semester in semesters]
template_data = dict(
semester_list=semester_list,
can_download_grades=request.user.can_download_grades,
)
return render(request, "student_index.html", template_data)
def test_distribution_without_general_grade_question(self):
baker.make(RatingAnswerCounter, question=self.question_grade, contribution=self.contribution1, answer=1, count=1)
baker.make(RatingAnswerCounter, question=self.question_grade, contribution=self.contribution1, answer=3, count=1)
baker.make(RatingAnswerCounter, question=self.question_grade, contribution=self.contribution2, answer=4, count=1)
baker.make(RatingAnswerCounter, question=self.question_grade, contribution=self.contribution2, answer=2, count=1)
baker.make(RatingAnswerCounter, question=self.question_likert, contribution=self.contribution1, answer=3, count=3)
baker.make(RatingAnswerCounter, question=self.question_likert, contribution=self.contribution1, answer=5, count=3)
baker.make(RatingAnswerCounter, question=self.question_likert, contribution=self.general_contribution, answer=5, count=5)
baker.make(RatingAnswerCounter, question=self.question_likert_2, contribution=self.general_contribution, answer=3, count=3)
cache_results(self.evaluation)
# contribution1: 0.4 * (0.5, 0, 0.5, 0, 0) + 0.6 * (0, 0, 0.5, 0, 0.5) = (0.2, 0, 0.5, 0, 0.3)
# contribution2: (0, 0.5, 0, 0.5, 0)
# contributions: (6 / 8) * (0.2, 0, 0.5, 0, 0.3) + (2 / 8) * (0, 0.5, 0, 0.5, 0) = (0.15, 0.125, 0.375, 0.125, 0.225)
# general_non_grade: (0, 0, 0.375, 0, 0.625)
# total: 0.375 * (0.15, 0.125, 0.375, 0.125, 0.225) + 0.625 * (0, 0, 0.375, 0, 0.625) = (0.05625, 0.046875, 0.375, 0.046875, 0.475)
distribution = calculate_average_distribution(self.evaluation)
self.assertAlmostEqual(distribution[0], 0.05625)
self.assertAlmostEqual(distribution[1], 0.046875)
self.assertAlmostEqual(distribution[2], 0.375)
self.assertAlmostEqual(distribution[3], 0.046875)
self.assertAlmostEqual(distribution[4], 0.475)
def test_average_grade(self):
question_grade2 = baker.make(Question, questionnaire=self.questionnaire, type=Question.GRADE)
baker.make(RatingAnswerCounter, question=self.question_grade, contribution=self.contribution1, answer=2, count=1)
baker.make(RatingAnswerCounter, question=self.question_grade, contribution=self.contribution2, answer=4, count=2)
baker.make(RatingAnswerCounter, question=question_grade2, contribution=self.contribution1, answer=1, count=1)
baker.make(RatingAnswerCounter, question=self.question_likert, contribution=self.contribution1, answer=3, count=4)
baker.make(RatingAnswerCounter, question=self.question_likert, contribution=self.general_contribution, answer=5, count=5)
baker.make(RatingAnswerCounter, question=self.question_likert_2, contribution=self.general_contribution, answer=3, count=3)
baker.make(RatingAnswerCounter, question=self.question_bipolar, contribution=self.general_contribution, answer=3, count=2)
baker.make(RatingAnswerCounter, question=self.question_bipolar_2, contribution=self.general_contribution, answer=-1, count=4)
cache_results(self.evaluation)
contributor_weights_sum = settings.CONTRIBUTOR_GRADE_QUESTIONS_WEIGHT + settings.CONTRIBUTOR_NON_GRADE_RATING_QUESTIONS_WEIGHT
contributor1_average = ((settings.CONTRIBUTOR_GRADE_QUESTIONS_WEIGHT * ((2 * 1) + (1 * 1)) / (1 + 1)) + (settings.CONTRIBUTOR_NON_GRADE_RATING_QUESTIONS_WEIGHT * 3)) / contributor_weights_sum # 2.4
contributor2_average = 4
contributors_average = ((4 * contributor1_average) + (2 * contributor2_average)) / (4 + 2) # 2.9333333
general_non_grade_average = ((5 * 5) + (3 * 3) + (2 * 5) + (4 * 7 / 3)) / (5 + 3 + 2 + 4) # 3.80952380
contributors_percentage = settings.CONTRIBUTIONS_WEIGHT / (settings.CONTRIBUTIONS_WEIGHT + settings.GENERAL_NON_GRADE_QUESTIONS_WEIGHT) # 0.375
general_non_grade_percentage = settings.GENERAL_NON_GRADE_QUESTIONS_WEIGHT / (settings.CONTRIBUTIONS_WEIGHT + settings.GENERAL_NON_GRADE_QUESTIONS_WEIGHT) # 0.625
total_grade = contributors_percentage * contributors_average + general_non_grade_percentage * general_non_grade_average # 1.1 + 2.38095238 = 3.48095238
average_grade = distribution_to_grade(calculate_average_distribution(self.evaluation))
self.assertAlmostEqual(average_grade, total_grade)
self.assertAlmostEqual(average_grade, 3.48095238)
def test_distribution_without_general_grade_question(self):
make_rating_answer_counters(self.question_grade, self.contribution1,
[1, 0, 1, 0, 0])
make_rating_answer_counters(self.question_grade, self.contribution2,
[0, 1, 0, 1, 0])
make_rating_answer_counters(self.question_likert, self.contribution1,
[0, 0, 3, 0, 3])
make_rating_answer_counters(self.question_likert,
self.general_contribution, [0, 0, 0, 0, 5])
make_rating_answer_counters(self.question_likert_2,
self.general_contribution, [0, 0, 3, 0, 0])
cache_results(self.evaluation)
# contribution1: 0.4 * (0.5, 0, 0.5, 0, 0) + 0.6 * (0, 0, 0.5, 0, 0.5) = (0.2, 0, 0.5, 0, 0.3)
# contribution2: (0, 0.5, 0, 0.5, 0)
# contributions: (6 / 8) * (0.2, 0, 0.5, 0, 0.3) + (2 / 8) * (0, 0.5, 0, 0.5, 0) = (0.15, 0.125, 0.375, 0.125, 0.225)
# general_non_grade: (0, 0, 0.375, 0, 0.625)
# total: 0.375 * (0.15, 0.125, 0.375, 0.125, 0.225) + 0.625 * (0, 0, 0.375, 0, 0.625) = (0.05625, 0.046875, 0.375, 0.046875, 0.475)
distribution = calculate_average_distribution(self.evaluation)
self.assertAlmostEqual(distribution[0], 0.05625)
self.assertAlmostEqual(distribution[1], 0.046875)
self.assertAlmostEqual(distribution[2], 0.375)
self.assertAlmostEqual(distribution[3], 0.046875)
self.assertAlmostEqual(distribution[4], 0.475)
def test_average_grade(self):
question_grade2 = mommy.make(Question, questionnaire=self.questionnaire, type="G")
mommy.make(RatingAnswerCounter, question=self.question_grade, contribution=self.contribution1, answer=2, count=1)
mommy.make(RatingAnswerCounter, question=self.question_grade, contribution=self.contribution2, answer=4, count=2)
mommy.make(RatingAnswerCounter, question=question_grade2, contribution=self.contribution1, answer=1, count=1)
mommy.make(RatingAnswerCounter, question=self.question_likert, contribution=self.contribution1, answer=3, count=4)
mommy.make(RatingAnswerCounter, question=self.question_likert, contribution=self.general_contribution, answer=5, count=5)
mommy.make(RatingAnswerCounter, question=self.question_likert_2, contribution=self.general_contribution, answer=3, count=3)
contributor_weights_sum = settings.CONTRIBUTOR_GRADE_QUESTIONS_WEIGHT + settings.CONTRIBUTOR_NON_GRADE_RATING_QUESTIONS_WEIGHT
contributor1_average = ((settings.CONTRIBUTOR_GRADE_QUESTIONS_WEIGHT * ((2 * 1) + (1 * 1)) / (1 + 1)) + (settings.CONTRIBUTOR_NON_GRADE_RATING_QUESTIONS_WEIGHT * 3)) / contributor_weights_sum # 2.4
contributor2_average = 4
contributors_average = ((4 * contributor1_average) + (2 * contributor2_average)) / (4 + 2) # 2.9333333
course_non_grade_average = ((5 * 5) + (3 * 3)) / (5 + 3) # 4.25
contributors_percentage = settings.CONTRIBUTIONS_WEIGHT / (settings.CONTRIBUTIONS_WEIGHT + settings.COURSE_NON_GRADE_QUESTIONS_WEIGHT) # 0.375
course_non_grade_percentage = settings.COURSE_NON_GRADE_QUESTIONS_WEIGHT / (settings.CONTRIBUTIONS_WEIGHT + settings.COURSE_NON_GRADE_QUESTIONS_WEIGHT) # 0.625
total_grade = contributors_percentage * contributors_average + course_non_grade_percentage * course_non_grade_average # 1.1 + 2.65625 = 3.75625
average_grade = distribution_to_grade(calculate_average_distribution(self.course))
self.assertAlmostEqual(average_grade, total_grade)
self.assertAlmostEqual(average_grade, 3.75625)
def test_distribution_with_general_grade_question(self):
make_rating_answer_counters(self.question_grade, self.contribution1,
[1, 0, 1, 0, 0])
make_rating_answer_counters(self.question_grade, self.contribution2,
[0, 1, 0, 1, 0])
make_rating_answer_counters(self.question_likert, self.contribution1,
[0, 0, 3, 0, 3])
make_rating_answer_counters(self.question_likert,
self.general_contribution, [0, 0, 0, 0, 5])
make_rating_answer_counters(self.question_likert_2,
self.general_contribution, [0, 0, 3, 0, 0])
make_rating_answer_counters(self.question_grade,
self.general_contribution,
[0, 10, 0, 0, 0])
cache_results(self.evaluation)
# contributions and general_non_grade are as above
# general_grade: (0, 1, 0, 0, 0)
# total: 0.3 * (0.15, 0.125, 0.375, 0.125, 0.225) + 0.2 * (0, 1, 0, 0, 0) + 0.5 * (0, 0, 0.375, 0, 0.625) = (0.045, 0.2375, 0.3, 0.0375, 0.38)
distribution = calculate_average_distribution(self.evaluation)
self.assertAlmostEqual(distribution[0], 0.045)
self.assertAlmostEqual(distribution[1], 0.2375)
self.assertAlmostEqual(distribution[2], 0.3)
self.assertAlmostEqual(distribution[3], 0.0375)
self.assertAlmostEqual(distribution[4], 0.38)
def test_distribution_with_general_grade_question(self):
baker.make(RatingAnswerCounter,
question=self.question_grade,
contribution=self.contribution1,
answer=1,
count=1)
baker.make(RatingAnswerCounter,
question=self.question_grade,
contribution=self.contribution1,
answer=3,
count=1)
baker.make(RatingAnswerCounter,
question=self.question_grade,
contribution=self.contribution2,
answer=4,
count=1)
baker.make(RatingAnswerCounter,
question=self.question_grade,
contribution=self.contribution2,
answer=2,
count=1)
baker.make(RatingAnswerCounter,
question=self.question_likert,
contribution=self.contribution1,
answer=3,
count=3)
baker.make(RatingAnswerCounter,
question=self.question_likert,
contribution=self.contribution1,
answer=5,
count=3)
baker.make(RatingAnswerCounter,
question=self.question_likert,
contribution=self.general_contribution,
answer=5,
count=5)
baker.make(RatingAnswerCounter,
question=self.question_likert_2,
contribution=self.general_contribution,
answer=3,
count=3)
baker.make(RatingAnswerCounter,
question=self.question_grade,
contribution=self.general_contribution,
answer=2,
count=10)
cache_results(self.evaluation)
# contributions and general_non_grade are as above
# general_grade: (0, 1, 0, 0, 0)
# total: 0.3 * (0.15, 0.125, 0.375, 0.125, 0.225) + 0.2 * (0, 1, 0, 0, 0) + 0.5 * (0, 0, 0.375, 0, 0.625) = (0.045, 0.2375, 0.3, 0.0375, 0.38)
distribution = calculate_average_distribution(self.evaluation)
self.assertAlmostEqual(distribution[0], 0.045)
self.assertAlmostEqual(distribution[1], 0.2375)
self.assertAlmostEqual(distribution[2], 0.3)
self.assertAlmostEqual(distribution[3], 0.0375)
self.assertAlmostEqual(distribution[4], 0.38)
def index(request):
user = request.user
show_delegated = get_parameter_from_url_or_session(request, "show_delegated", True)
contributor_visible_states = ['prepared', 'editor_approved', 'approved', 'in_evaluation', 'evaluated', 'reviewed', 'published']
own_courses = Course.objects.filter(
Q(evaluations__state__in=contributor_visible_states) & (
Q(responsibles=user) |
Q(evaluations__contributions__contributor=user)
)
)
own_evaluations = [evaluation for course in own_courses for evaluation in course.evaluations.all() if evaluation.can_be_seen_by(user)]
for evaluation in own_evaluations:
evaluation.contributes_to = evaluation.contributions.filter(contributor=user).exists()
displayed_evaluations = set(own_evaluations)
if show_delegated:
represented_users = user.represented_users.all()
delegated_courses = Course.objects.filter(
Q(evaluations__state__in=contributor_visible_states) & (
Q(responsibles__in=represented_users) |
Q(
evaluations__contributions__role=Contribution.Role.EDITOR,
evaluations__contributions__contributor__in=represented_users,
)
)
)
delegated_evaluations = set(evaluation for course in delegated_courses for evaluation in course.evaluations.all() if evaluation.can_be_seen_by(user))
for evaluation in delegated_evaluations:
evaluation.delegated_evaluation = True
displayed_evaluations |= delegated_evaluations - displayed_evaluations
displayed_evaluations = list(displayed_evaluations)
displayed_evaluations.sort(key=lambda evaluation: (evaluation.course.name, evaluation.name)) # evaluations must be sorted for regrouping them in the template
for evaluation in displayed_evaluations:
if evaluation.state == "published":
if not evaluation.is_single_result:
evaluation.distribution = calculate_average_distribution(evaluation)
else:
evaluation.single_result_rating_result = get_single_result_rating_result(evaluation)
evaluation.distribution = normalized_distribution(evaluation.single_result_rating_result.counts)
evaluation.avg_grade = distribution_to_grade(evaluation.distribution)
displayed_evaluations = get_evaluations_with_course_result_attributes(displayed_evaluations)
semesters = Semester.objects.all()
semester_list = [dict(
semester_name=semester.name,
id=semester.id,
is_active=semester.is_active,
evaluations=[evaluation for evaluation in displayed_evaluations if evaluation.course.semester_id == semester.id]
) for semester in semesters]
template_data = dict(
semester_list=semester_list,
show_delegated=show_delegated,
delegate_selection_form=DelegateSelectionForm(),
)
return render(request, "contributor_index.html", template_data)
def test_average_grade(self):
question_grade2 = baker.make(Question,
questionnaire=self.questionnaire,
type=Question.GRADE)
make_rating_answer_counters(self.question_grade, self.contribution1,
[0, 1, 0, 0, 0])
make_rating_answer_counters(self.question_grade, self.contribution2,
[0, 0, 0, 2, 0])
make_rating_answer_counters(question_grade2, self.contribution1,
[1, 0, 0, 0, 0])
make_rating_answer_counters(self.question_likert, self.contribution1,
[0, 0, 4, 0, 0])
make_rating_answer_counters(self.question_likert,
self.general_contribution, [0, 0, 0, 0, 5])
make_rating_answer_counters(self.question_likert_2,
self.general_contribution, [0, 0, 3, 0, 0])
make_rating_answer_counters(self.question_bipolar,
self.general_contribution,
[0, 0, 0, 0, 0, 0, 2])
make_rating_answer_counters(self.question_bipolar_2,
self.general_contribution,
[0, 0, 4, 0, 0, 0, 0])
cache_results(self.evaluation)
contributor_weights_sum = (
settings.CONTRIBUTOR_GRADE_QUESTIONS_WEIGHT +
settings.CONTRIBUTOR_NON_GRADE_RATING_QUESTIONS_WEIGHT)
contributor1_average = (
(settings.CONTRIBUTOR_GRADE_QUESTIONS_WEIGHT *
((2 * 1) + (1 * 1)) / (1 + 1)) +
(settings.CONTRIBUTOR_NON_GRADE_RATING_QUESTIONS_WEIGHT *
3)) / contributor_weights_sum # 2.4
contributor2_average = 4
contributors_average = (
(4 * contributor1_average) +
(2 * contributor2_average)) / (4 + 2) # 2.9333333
general_non_grade_average = (
(5 * 5) + (3 * 3) + (2 * 5) +
(4 * 7 / 3)) / (5 + 3 + 2 + 4) # 3.80952380
contributors_percentage = settings.CONTRIBUTIONS_WEIGHT / (
settings.CONTRIBUTIONS_WEIGHT +
settings.GENERAL_NON_GRADE_QUESTIONS_WEIGHT) # 0.375
general_non_grade_percentage = settings.GENERAL_NON_GRADE_QUESTIONS_WEIGHT / (
settings.CONTRIBUTIONS_WEIGHT +
settings.GENERAL_NON_GRADE_QUESTIONS_WEIGHT) # 0.625
total_grade = (contributors_percentage * contributors_average +
general_non_grade_percentage * general_non_grade_average
) # 1.1 + 2.38095238 = 3.48095238
average_grade = distribution_to_grade(
calculate_average_distribution(self.evaluation))
self.assertAlmostEqual(average_grade, total_grade)
self.assertAlmostEqual(average_grade, 3.48095238)
def index(request):
# retrieve all courses which have evaluations that are not in state "new" and in which the user participates
courses = Course.objects.filter(
evaluations__participants=request.user,
evaluations__state__in=[
'prepared', 'editor_approved', 'approved', 'in_evaluation',
'evaluated', 'reviewed', 'published'
]).distinct().prefetch_related('semester', 'grade_documents', 'type',
'evaluations',
'evaluations__participants',
'evaluations__voters')
# retrieve all evaluations which the user can see that are not new
evaluations = [
evaluation for course in courses
for evaluation in course.evaluations.all()
if evaluation.can_be_seen_by(request.user)
]
for evaluation in evaluations:
if evaluation.state == "published":
if not evaluation.is_single_result:
evaluation.distribution = calculate_average_distribution(
evaluation)
else:
evaluation.single_result_rating_result = get_single_result_rating_result(
evaluation)
evaluation.distribution = normalized_distribution(
evaluation.single_result_rating_result.counts)
evaluation.avg_grade = distribution_to_grade(
evaluation.distribution)
evaluation.participates_in = request.user in evaluation.participants.all(
)
evaluation.voted_for = request.user in evaluation.voters.all()
evaluations = get_evaluations_with_course_result_attributes(evaluations)
evaluations.sort(
key=lambda evaluation: (evaluation.course.name, evaluation.name)
) # evaluations must be sorted for regrouping them in the template
semesters = Semester.objects.all()
semester_list = [
dict(semester_name=semester.name,
id=semester.id,
is_active=semester.is_active,
results_are_archived=semester.results_are_archived,
grade_documents_are_deleted=semester.grade_documents_are_deleted,
evaluations=[
evaluation for evaluation in evaluations
if evaluation.course.semester_id == semester.id
]) for semester in semesters
]
template_data = dict(
semester_list=semester_list,
can_download_grades=request.user.can_download_grades,
)
return render(request, "student_index.html", template_data)
def test_get_single_result_rating_result(self):
single_result_evaluation = mommy.make(Evaluation, state='published', is_single_result=True)
questionnaire = Questionnaire.objects.get(name_en=Questionnaire.SINGLE_RESULT_QUESTIONNAIRE_NAME)
contribution = mommy.make(Contribution, contributor=mommy.make(UserProfile), evaluation=single_result_evaluation, questionnaires=[questionnaire], can_edit=True, textanswer_visibility=Contribution.GENERAL_TEXTANSWERS)
mommy.make(RatingAnswerCounter, question=questionnaire.questions.first(), contribution=contribution, answer=1, count=1)
mommy.make(RatingAnswerCounter, question=questionnaire.questions.first(), contribution=contribution, answer=4, count=1)
distribution = calculate_average_distribution(single_result_evaluation)
self.assertEqual(distribution, (0.5, 0, 0, 0.5, 0))
rating_result = get_single_result_rating_result(single_result_evaluation)
self.assertEqual(rating_result.counts, (1, 0, 0, 1, 0))
def test_get_single_result_rating_result(self):
single_result_course = mommy.make(Course, state='published', is_single_result=True)
questionnaire = Questionnaire.objects.get(name_en=Questionnaire.SINGLE_RESULT_QUESTIONNAIRE_NAME)
contribution = mommy.make(Contribution, contributor=mommy.make(UserProfile), course=single_result_course, questionnaires=[questionnaire], responsible=True, can_edit=True, comment_visibility=Contribution.ALL_COMMENTS)
mommy.make(RatingAnswerCounter, question=questionnaire.question_set.first(), contribution=contribution, answer=1, count=1)
mommy.make(RatingAnswerCounter, question=questionnaire.question_set.first(), contribution=contribution, answer=4, count=1)
distribution = calculate_average_distribution(single_result_course)
self.assertEqual(distribution, (0.5, 0, 0, 0.5, 0))
rating_result = get_single_result_rating_result(single_result_course)
self.assertEqual(rating_result.counts, (1, 0, 0, 1, 0))
def write_overall_results(self, evaluations_with_results,
course_results_exist):
evaluations = [e for e, __ in evaluations_with_results]
self.write_cell(_("Overall Average Grade"), "bold")
averages = (distribution_to_grade(calculate_average_distribution(e))
for e in evaluations)
self.write_row(
averages, lambda avg: self.grade_to_style(avg)
if avg else "border_left_right")
self.write_cell(_("Total voters/Total participants"), "bold")
voter_ratios = (f"{e.num_voters}/{e.num_participants}"
for e in evaluations)
self.write_row(voter_ratios, style="total_voters")
self.write_cell(_("Evaluation rate"), "bold")
# round down like in progress bar
participant_percentages = (
f"{int((e.num_voters / e.num_participants) * 100) if e.num_participants > 0 else 0}%"
for e in evaluations)
self.write_row(participant_percentages, style="evaluation_rate")
if course_results_exist:
# Only query the number of evaluations once and keep track of it here.
count_gt_1 = [e.course_evaluations_count > 1 for e in evaluations]
# Borders only if there is a course grade below. Offset by one column
self.write_empty_row_with_styles(["default"] + [
"border_left_right" if gt1 else "default" for gt1 in count_gt_1
])
self.write_cell(_("Evaluation weight"), "bold")
weight_percentages = (f"{e.weight_percentage}%" if gt1 else None
for e, gt1 in zip(evaluations, count_gt_1))
self.write_row(
weight_percentages, lambda s: "evaluation_weight"
if s is not None else "default")
self.write_cell(_("Course Grade"), "bold")
for evaluation, gt1 in zip(evaluations, count_gt_1):
if not gt1:
self.write_cell()
continue
avg = evaluation.course.avg_grade
style = self.grade_to_style(
avg) if avg is not None else "border_left_right"
self.write_cell(avg, style)
self.next_row()
# Same reasoning as above.
self.write_empty_row_with_styles(
["default"] +
["border_top" if gt1 else "default" for gt1 in count_gt_1])
def index(request):
user = request.user
show_delegated = get_parameter_from_url_or_session(request, "show_delegated", True)
contributor_visible_states = ['prepared', 'editor_approved', 'approved', 'in_evaluation', 'evaluated', 'reviewed', 'published']
own_courses = Course.objects.filter(
Q(evaluations__state__in=contributor_visible_states) & (
Q(responsibles=user) |
Q(evaluations__contributions__contributor=user)
)
)
own_evaluations = [evaluation for course in own_courses for evaluation in course.evaluations.all() if evaluation.can_be_seen_by(user)]
for evaluation in own_evaluations:
evaluation.contributes_to = evaluation.contributions.filter(contributor=user).exists()
displayed_evaluations = set(own_evaluations)
if show_delegated:
represented_users = user.represented_users.all()
delegated_courses = Course.objects.filter(
Q(evaluations__state__in=contributor_visible_states) & (
Q(responsibles__in=represented_users) |
Q(evaluations__contributions__can_edit=True, evaluations__contributions__contributor__in=represented_users)
)
)
delegated_evaluations = set(evaluation for course in delegated_courses for evaluation in course.evaluations.all() if evaluation.can_be_seen_by(user))
for evaluation in delegated_evaluations:
evaluation.delegated_evaluation = True
displayed_evaluations |= delegated_evaluations - displayed_evaluations
displayed_evaluations = list(displayed_evaluations)
displayed_evaluations.sort(key=lambda evaluation: evaluation.full_name) # evaluations must be sorted for regrouping them in the template
for evaluation in displayed_evaluations:
if evaluation.state == "published":
if not evaluation.is_single_result:
evaluation.distribution = calculate_average_distribution(evaluation)
evaluation.avg_grade = distribution_to_grade(evaluation.distribution)
else:
evaluation.single_result_rating_result = get_single_result_rating_result(evaluation)
displayed_evaluations = get_evaluations_with_course_result_attributes(displayed_evaluations)
semesters = Semester.objects.all()
semester_list = [dict(
semester_name=semester.name,
id=semester.id,
is_active_semester=semester.is_active_semester,
evaluations=[evaluation for evaluation in displayed_evaluations if evaluation.course.semester_id == semester.id]
) for semester in semesters]
template_data = dict(
semester_list=semester_list,
show_delegated=show_delegated,
delegate_selection_form=DelegateSelectionForm(),
)
return render(request, "contributor_index.html", template_data)
def test_result_calculation_with_no_contributor_rating_question_does_not_fail(self):
evaluation = mommy.make(Evaluation, state='published', participants=[self.student1, self.student2], voters=[self.student1, self.student2])
questionnaire_text = mommy.make(Questionnaire)
mommy.make(Question, questionnaire=questionnaire_text, type=Question.TEXT)
mommy.make(Contribution, contributor=mommy.make(UserProfile), evaluation=evaluation, questionnaires=[questionnaire_text])
evaluation.general_contribution.questionnaires.set([self.questionnaire])
mommy.make(RatingAnswerCounter, question=self.question_grade, contribution=evaluation.general_contribution, answer=1, count=1)
distribution = calculate_average_distribution(evaluation)
self.assertEqual(distribution[0], 1)
def index(request):
user = request.user
show_delegated = get_parameter_from_url_or_session(request,
"show_delegated", True)
contributor_visible_states = [
'prepared', 'editor_approved', 'approved', 'in_evaluation',
'evaluated', 'reviewed', 'published'
]
own_evaluations = Evaluation.objects.filter(
contributions__contributor=user, state__in=contributor_visible_states)
displayed_evaluations = list(own_evaluations)
if show_delegated:
represented_users = user.represented_users.all()
delegated_evaluations = Evaluation.objects.exclude(
id__in=own_evaluations).filter(
contributions__can_edit=True,
contributions__contributor__in=represented_users,
state__in=contributor_visible_states)
for evaluation in delegated_evaluations:
evaluation.delegated_evaluation = True
displayed_evaluations += list(delegated_evaluations)
displayed_evaluations.sort(key=lambda evaluation: list(STATES_ORDERED.keys(
)).index(evaluation.state))
delegate_selection_form = DelegateSelectionForm()
for evaluation in displayed_evaluations:
evaluation.distribution = calculate_average_distribution(evaluation)
evaluation.avg_grade = distribution_to_grade(evaluation.distribution)
semesters = Semester.objects.all()
semester_list = [
dict(semester_name=semester.name,
id=semester.id,
is_active_semester=semester.is_active_semester,
evaluations=[
evaluation for evaluation in displayed_evaluations
if evaluation.course.semester_id == semester.id
]) for semester in semesters
]
template_data = dict(
semester_list=semester_list,
show_delegated=show_delegated,
delegate_selection_form=delegate_selection_form,
)
return render(request, "contributor_index.html", template_data)
def index(request):
# retrieve all evaluations, where the user is a participant and that are not new
evaluations = list(
set(
Evaluation.objects.filter(participants=request.user).exclude(
state="new")))
for evaluation in evaluations:
evaluation.distribution = calculate_average_distribution(evaluation)
evaluation.avg_grade = distribution_to_grade(evaluation.distribution)
voted_evaluations = list(
set(Evaluation.objects.filter(voters=request.user)))
due_evaluations = list(
set(
Evaluation.objects.filter(
participants=request.user,
state='in_evaluation').exclude(voters=request.user)))
# due evaluations come first, then everything else in chronological order
# some states are handled as a group because they appear the same to students
def sorter(evaluation):
return (evaluation not in due_evaluations, evaluation.state
not in ['prepared', 'editor_approved',
'approved'], evaluation.state != 'in_evaluation',
evaluation.state not in ['evaluated',
'reviewed'], evaluation.name)
evaluations.sort(key=sorter)
semesters = Semester.objects.all()
semester_list = [
dict(semester_name=semester.name,
id=semester.id,
is_active_semester=semester.is_active_semester,
results_are_archived=semester.results_are_archived,
grade_documents_are_deleted=semester.grade_documents_are_deleted,
evaluations=[
evaluation for evaluation in evaluations
if evaluation.course.semester_id == semester.id
]) for semester in semesters
]
template_data = dict(
semester_list=semester_list,
voted_evaluations=voted_evaluations,
can_download_grades=request.user.can_download_grades,
)
return render(request, "student_index.html", template_data)
def index(request):
# retrieve all courses, where the user is a participant and that are not new
courses = list(
set(
Course.objects.filter(participants=request.user).exclude(
state="new")))
for course in courses:
course.distribution = calculate_average_distribution(course)
course.avg_grade = distribution_to_grade(course.distribution)
voted_courses = list(set(Course.objects.filter(voters=request.user)))
due_courses = list(
set(
Course.objects.filter(
participants=request.user,
state='in_evaluation').exclude(voters=request.user)))
# due courses come first, then everything else in chronological order
# some states are handled as a group because they appear the same to students
sorter = lambda course: (course not in due_courses, course.state not in [
'prepared', 'editor_approved', 'approved'
], course.state != 'in_evaluation', course.state not in
['evaluated', 'reviewed'], course.name)
courses.sort(key=sorter)
semesters = Semester.objects.all()
semester_list = [
dict(semester_name=semester.name,
id=semester.id,
is_active_semester=semester.is_active_semester,
results_are_archived=semester.results_are_archived,
courses=[
course for course in courses
if course.semester_id == semester.id
]) for semester in semesters
]
template_data = dict(
semester_list=semester_list,
voted_courses=voted_courses,
can_download_grades=request.user.can_download_grades,
)
return render(request, "student_index.html", template_data)
def get_courses_with_prefetched_data(courses):
if isinstance(courses, QuerySet):
courses = (courses
.annotate(num_participants=Count("participants", distinct=True), num_voters=Count("voters", distinct=True))
.select_related("type")
.prefetch_related(
"degrees",
"semester",
Prefetch("contributions", queryset=Contribution.objects.filter(responsible=True).select_related("contributor"), to_attr="responsible_contributions")
)
)
for course in courses:
course.responsible_contributors = [contribution.contributor for contribution in course.responsible_contributions]
for course in courses:
if not course.is_single_result:
course.distribution = calculate_average_distribution(course)
course.avg_grade = distribution_to_grade(course.distribution)
else:
course.single_result_rating_result = get_single_result_rating_result(course)
return courses
def get_evaluations_with_prefetched_data(evaluations):
if isinstance(evaluations, QuerySet):
evaluations = (evaluations
.select_related("course__type")
.prefetch_related(
"course__degrees",
"course__semester",
"course__responsibles",
)
)
evaluations = Evaluation.annotate_with_participant_and_voter_counts(evaluations)
for evaluation in evaluations:
if not evaluation.is_single_result:
evaluation.distribution = calculate_average_distribution(evaluation)
else:
evaluation.single_result_rating_result = get_single_result_rating_result(evaluation)
evaluation.distribution = normalized_distribution(evaluation.single_result_rating_result.counts)
evaluation.avg_grade = distribution_to_grade(evaluation.distribution)
return evaluations
def test_distribution_with_general_grade_question(self):
mommy.make(RatingAnswerCounter, question=self.question_grade, contribution=self.contribution1, answer=1, count=1)
mommy.make(RatingAnswerCounter, question=self.question_grade, contribution=self.contribution1, answer=3, count=1)
mommy.make(RatingAnswerCounter, question=self.question_grade, contribution=self.contribution2, answer=4, count=1)
mommy.make(RatingAnswerCounter, question=self.question_grade, contribution=self.contribution2, answer=2, count=1)
mommy.make(RatingAnswerCounter, question=self.question_likert, contribution=self.contribution1, answer=3, count=3)
mommy.make(RatingAnswerCounter, question=self.question_likert, contribution=self.contribution1, answer=5, count=3)
mommy.make(RatingAnswerCounter, question=self.question_likert, contribution=self.general_contribution, answer=5, count=5)
mommy.make(RatingAnswerCounter, question=self.question_likert_2, contribution=self.general_contribution, answer=3, count=3)
mommy.make(RatingAnswerCounter, question=self.question_grade, contribution=self.general_contribution, answer=2, count=10)
# contributions and general_non_grade are as above
# general_grade: (0, 1, 0, 0, 0)
# total: 0.3 * (0.15, 0.125, 0.375, 0.125, 0.225) + 0.2 * (0, 1, 0, 0, 0) + 0.5 * (0, 0, 0.375, 0, 0.625) = (0.045, 0.2375, 0.3, 0.0375, 0.38)
distribution = calculate_average_distribution(self.evaluation)
self.assertAlmostEqual(distribution[0], 0.045)
self.assertAlmostEqual(distribution[1], 0.2375)
self.assertAlmostEqual(distribution[2], 0.3)
self.assertAlmostEqual(distribution[3], 0.0375)
self.assertAlmostEqual(distribution[4], 0.38)
def index(request):
user = request.user
contributor_visible_states = [
'prepared', 'editor_approved', 'approved', 'in_evaluation',
'evaluated', 'reviewed', 'published'
]
own_courses = Course.objects.filter(contributions__contributor=user,
state__in=contributor_visible_states)
represented_users = user.represented_users.all()
delegated_courses = Course.objects.exclude(id__in=own_courses).filter(
contributions__can_edit=True,
contributions__contributor__in=represented_users,
state__in=contributor_visible_states)
all_courses = list(own_courses) + list(delegated_courses)
all_courses.sort(
key=lambda course: list(STATES_ORDERED.keys()).index(course.state))
for course in all_courses:
course.distribution = calculate_average_distribution(
course) if course.can_user_see_grades(user) else None
course.avg_grade = distribution_to_grade(course.distribution)
semesters = Semester.objects.all()
semester_list = [
dict(semester_name=semester.name,
id=semester.id,
is_active_semester=semester.is_active_semester,
courses=[
course for course in all_courses
if course.semester_id == semester.id
]) for semester in semesters
]
template_data = dict(semester_list=semester_list,
delegated_courses=delegated_courses)
return render(request, "contributor_index.html", template_data)
def semester_detail(request, semester_id):
semester = get_object_or_404(Semester, id=semester_id)
visible_states = ['published']
if request.user.is_reviewer:
visible_states += ['in_evaluation', 'evaluated', 'reviewed']
courses = semester.course_set.filter(
state__in=visible_states).prefetch_related("degrees")
courses = [
course for course in courses
if course.can_user_see_course(request.user)
]
for course in courses:
course.distribution = calculate_average_distribution(
course) if course.can_user_see_grades(request.user) else None
course.avg_grade = distribution_to_grade(course.distribution)
CourseTuple = namedtuple('CourseTuple', ('courses', 'single_results'))
courses_by_degree = OrderedDict()
for degree in Degree.objects.all():
courses_by_degree[degree] = CourseTuple([], [])
for course in courses:
if course.is_single_result:
for degree in course.degrees.all():
section = calculate_results(course)[0]
result = section.results[0]
courses_by_degree[degree].single_results.append(
(course, result))
else:
for degree in course.degrees.all():
courses_by_degree[degree].courses.append(course)
template_data = dict(semester=semester,
courses_by_degree=courses_by_degree)
return render(request, "results_semester_detail.html", template_data)
def test_get_single_result_rating_result(self):
single_result_evaluation = baker.make(Evaluation,
state=Evaluation.State.PUBLISHED,
is_single_result=True)
questionnaire = Questionnaire.single_result_questionnaire()
contribution = baker.make(
Contribution,
contributor=baker.make(UserProfile),
evaluation=single_result_evaluation,
questionnaires=[questionnaire],
role=Contribution.Role.EDITOR,
textanswer_visibility=Contribution.TextAnswerVisibility.
GENERAL_TEXTANSWERS,
)
make_rating_answer_counters(questionnaire.questions.first(),
contribution, [1, 0, 0, 1, 0])
cache_results(single_result_evaluation)
distribution = calculate_average_distribution(single_result_evaluation)
self.assertEqual(distribution, (0.5, 0, 0, 0.5, 0))
rating_result = get_single_result_rating_result(
single_result_evaluation)
self.assertEqual(rating_result.counts, (1, 0, 0, 1, 0))
def index(request):
# retrieve all courses, where the user is a participant and that are not new
courses = list(set(Course.objects.filter(participants=request.user).exclude(state="new")))
for course in courses:
course.distribution = calculate_average_distribution(course)
course.avg_grade = distribution_to_grade(course.distribution)
voted_courses = list(set(Course.objects.filter(voters=request.user)))
due_courses = list(set(Course.objects.filter(participants=request.user, state='in_evaluation').exclude(voters=request.user)))
# due courses come first, then everything else in chronological order
# some states are handled as a group because they appear the same to students
sorter = lambda course: (
course not in due_courses,
course.state not in ['prepared', 'editor_approved', 'approved'],
course.state != 'in_evaluation',
course.state not in ['evaluated', 'reviewed'],
course.name
)
courses.sort(key=sorter)
semesters = Semester.objects.all()
semester_list = [dict(
semester_name=semester.name,
id=semester.id,
is_active_semester=semester.is_active_semester,
results_are_archived=semester.results_are_archived,
grade_documents_are_deleted=semester.grade_documents_are_deleted,
courses=[course for course in courses if course.semester_id == semester.id]
) for semester in semesters]
template_data = dict(
semester_list=semester_list,
voted_courses=voted_courses,
can_download_grades=request.user.can_download_grades,
)
return render(request, "student_index.html", template_data)
def get_evaluations_with_prefetched_data(evaluations):
if isinstance(evaluations, QuerySet):
# these annotates and the zip below could be replaced by something like this, but it was 2x slower:
# annotate(num_participants=Coalesce('_participant_count', Count("participants", distinct=True)))
participant_counts = evaluations.annotate(
num_participants=Count("participants")).order_by('pk').values_list(
"num_participants", flat=True)
voter_counts = evaluations.annotate(
num_voters=Count("voters")).order_by('pk').values_list(
"num_voters", flat=True)
course_evaluations_counts = evaluations.annotate(
num_course_evaluations=Count("course__evaluations")).order_by(
'pk').values_list("num_course_evaluations", flat=True)
evaluations = (
evaluations.select_related("course__type").prefetch_related(
"course__degrees",
"course__semester",
"course__responsibles",
))
for evaluation, participant_count, voter_count, course_evaluations_count in zip(
evaluations, participant_counts, voter_counts,
course_evaluations_counts):
if evaluation._participant_count is None:
evaluation.num_participants = participant_count
evaluation.num_voters = voter_count
evaluation.course_evaluations_count = course_evaluations_count
for evaluation in evaluations:
if not evaluation.is_single_result:
evaluation.distribution = calculate_average_distribution(
evaluation)
else:
evaluation.single_result_rating_result = get_single_result_rating_result(
evaluation)
evaluation.distribution = normalized_distribution(
evaluation.single_result_rating_result.counts)
evaluation.avg_grade = distribution_to_grade(evaluation.distribution)
return evaluations
def get_evaluations_of_course(course, request):
course_evaluations = []
if course.evaluations.count() > 1:
course_evaluations = [
evaluation
for evaluation in course.evaluations.filter(state=Evaluation.State.PUBLISHED)
if evaluation.can_be_seen_by(request.user)
]
if request.user.is_reviewer:
course_evaluations += course.evaluations.filter(
state__in=[Evaluation.State.IN_EVALUATION, Evaluation.State.EVALUATED, Evaluation.State.REVIEWED]
)
course_evaluations = get_evaluations_with_course_result_attributes(course_evaluations)
for course_evaluation in course_evaluations:
if course_evaluation.is_single_result:
course_evaluation.single_result_rating_result = get_single_result_rating_result(course_evaluation)
else:
course_evaluation.distribution = calculate_average_distribution(course_evaluation)
course_evaluation.avg_grade = distribution_to_grade(course_evaluation.distribution)
return course_evaluations
def test_distribution_without_general_grade_question(self):
mommy.make(RatingAnswerCounter, question=self.question_grade, contribution=self.contribution1, answer=1, count=1)
mommy.make(RatingAnswerCounter, question=self.question_grade, contribution=self.contribution1, answer=3, count=1)
mommy.make(RatingAnswerCounter, question=self.question_grade, contribution=self.contribution2, answer=4, count=1)
mommy.make(RatingAnswerCounter, question=self.question_grade, contribution=self.contribution2, answer=2, count=1)
mommy.make(RatingAnswerCounter, question=self.question_likert, contribution=self.contribution1, answer=3, count=3)
mommy.make(RatingAnswerCounter, question=self.question_likert, contribution=self.contribution1, answer=5, count=3)
mommy.make(RatingAnswerCounter, question=self.question_likert, contribution=self.general_contribution, answer=5, count=5)
mommy.make(RatingAnswerCounter, question=self.question_likert_2, contribution=self.general_contribution, answer=3, count=3)
# contribution1: 0.4 * (0.5, 0, 0.5, 0, 0) + 0.6 * (0, 0, 0.5, 0, 0.5) = (0.2, 0, 0.5, 0, 0.3)
# contribution2: (0, 0.5, 0, 0.5, 0)
# contributions: (6 / 8) * (0.2, 0, 0.5, 0, 0.3) + (2 / 8) * (0, 0.5, 0, 0.5, 0) = (0.15, 0.125, 0.375, 0.125, 0.225)
# general_non_grade: (0, 0, 0.375, 0, 0.625)
# total: 0.375 * (0.15, 0.125, 0.375, 0.125, 0.225) + 0.625 * (0, 0, 0.375, 0, 0.625) = (0.05625, 0.046875, 0.375, 0.046875, 0.475)
distribution = calculate_average_distribution(self.evaluation)
self.assertAlmostEqual(distribution[0], 0.05625)
self.assertAlmostEqual(distribution[1], 0.046875)
self.assertAlmostEqual(distribution[2], 0.375)
self.assertAlmostEqual(distribution[3], 0.046875)
self.assertAlmostEqual(distribution[4], 0.475)
def evaluation_detail(request, semester_id, evaluation_id):
semester = get_object_or_404(Semester, id=semester_id)
evaluation = get_object_or_404(semester.evaluations,
id=evaluation_id,
course__semester=semester)
if not evaluation.can_user_see_results_page(request.user):
raise PermissionDenied
evaluation_result = collect_results(evaluation)
if request.user.is_reviewer:
view = request.GET.get(
'view', 'public') # if parameter is not given, show public view.
else:
view = request.GET.get(
'view', 'full') # if parameter is not given, show own view.
if view not in ['public', 'full', 'export']:
view = 'public'
view_as_user = request.user
if view == 'export' and request.user.is_staff:
view_as_user = UserProfile.objects.get(
id=int(request.GET.get('contributor_id', request.user.id)))
represented_users = [view_as_user]
if view != 'export':
represented_users += list(view_as_user.represented_users.all())
# redirect to non-public view if there is none because the results have not been published
if not evaluation.can_publish_rating_results and view == 'public':
view = 'full'
# remove text answers if the user may not see them
for questionnaire_result in evaluation_result.questionnaire_results:
for question_result in questionnaire_result.question_results:
if isinstance(question_result, TextResult):
question_result.answers = [
answer for answer in question_result.answers
if user_can_see_textanswer(view_as_user, represented_users,
answer, view)
]
# remove empty TextResults
questionnaire_result.question_results = [
result for result in questionnaire_result.question_results
if not isinstance(result, TextResult) or len(result.answers) > 0
]
# filter empty headings
for questionnaire_result in evaluation_result.questionnaire_results:
filtered_question_results = []
for index, question_result in enumerate(
questionnaire_result.question_results):
# filter out if there are no more questions or the next question is also a heading question
if isinstance(question_result, HeadingResult):
if index == len(questionnaire_result.question_results
) - 1 or isinstance(
questionnaire_result.question_results[index
+ 1],
HeadingResult):
continue
filtered_question_results.append(question_result)
questionnaire_result.question_results = filtered_question_results
# remove empty questionnaire_results and contribution_results
for contribution_result in evaluation_result.contribution_results:
contribution_result.questionnaire_results = [
questionnaire_result for questionnaire_result in
contribution_result.questionnaire_results
if questionnaire_result.question_results
]
evaluation_result.contribution_results = [
contribution_result
for contribution_result in evaluation_result.contribution_results
if contribution_result.questionnaire_results
]
add_warnings(evaluation, evaluation_result)
# split evaluation_result into different lists
general_questionnaire_results_top = []
general_questionnaire_results_bottom = []
contributor_contribution_results = []
for contribution_result in evaluation_result.contribution_results:
if contribution_result.contributor is None:
for questionnaire_result in contribution_result.questionnaire_results:
if questionnaire_result.questionnaire.is_below_contributors:
general_questionnaire_results_bottom.append(
questionnaire_result)
else:
general_questionnaire_results_top.append(
questionnaire_result)
elif view != 'export' or view_as_user.id == contribution_result.contributor.id:
contributor_contribution_results.append(contribution_result)
if not contributor_contribution_results:
general_questionnaire_results_top += general_questionnaire_results_bottom
general_questionnaire_results_bottom = []
course_evaluations = []
if evaluation.course.evaluations.count() > 1:
course_evaluations = [
evaluation for evaluation in evaluation.course.evaluations.filter(
state="published")
if evaluation.can_user_see_evaluation(request.user)
]
if request.user.is_reviewer:
course_evaluations += evaluation.course.evaluations.filter(
state__in=['in_evaluation', 'evaluated', 'reviewed'])
course_evaluations = get_evaluations_with_course_result_attributes(
course_evaluations)
for course_evaluation in course_evaluations:
if course_evaluation.is_single_result:
course_evaluation.single_result_rating_result = get_single_result_rating_result(
course_evaluation)
else:
course_evaluation.distribution = calculate_average_distribution(
course_evaluation)
course_evaluation.avg_grade = distribution_to_grade(
course_evaluation.distribution)
other_contributors = []
if view == 'export':
other_contributors = [
contribution_result.contributor
for contribution_result in evaluation_result.contribution_results
if contribution_result.contributor not in [None, view_as_user]
]
# if the evaluation is not published, the rendered results are not cached, so we need to attach distribution
# information for rendering the distribution bar
if evaluation.state != 'published':
evaluation = get_evaluations_with_prefetched_data([evaluation])[0]
template_data = dict(
evaluation=evaluation,
course=evaluation.course,
course_evaluations=course_evaluations,
general_questionnaire_results_top=general_questionnaire_results_top,
general_questionnaire_results_bottom=
general_questionnaire_results_bottom,
contributor_contribution_results=contributor_contribution_results,
is_reviewer=view_as_user.is_reviewer,
is_contributor=evaluation.is_user_contributor(view_as_user),
is_responsible_or_contributor_or_delegate=evaluation.
is_user_responsible_or_contributor_or_delegate(view_as_user),
can_download_grades=view_as_user.can_download_grades,
view=view,
view_as_user=view_as_user,
other_contributors=other_contributors,
)
return render(request, "results_evaluation_detail.html", template_data)
def course_detail(request, semester_id, course_id):
semester = get_object_or_404(Semester, id=semester_id)
course = get_object_or_404(semester.course_set, id=course_id, semester=semester)
if not course.can_user_see_results_page(request.user):
raise PermissionDenied
course_result = collect_results(course)
if request.user.is_reviewer:
public_view = request.GET.get('public_view') != 'false' # if parameter is not given, show public view.
else:
public_view = request.GET.get('public_view') == 'true' # if parameter is not given, show own view.
# redirect to non-public view if there is none because the results have not been published
if not course.can_publish_rating_results:
public_view = False
represented_users = list(request.user.represented_users.all()) + [request.user]
# remove text answers if the user may not see them
for questionnaire_result in course_result.questionnaire_results:
for question_result in questionnaire_result.question_results:
if isinstance(question_result, TextResult):
question_result.answers = [answer for answer in question_result.answers if user_can_see_text_answer(request.user, represented_users, answer, public_view)]
# remove empty TextResults
questionnaire_result.question_results = [result for result in questionnaire_result.question_results if not isinstance(result, TextResult) or len(result.answers) > 0]
# filter empty headings
for questionnaire_result in course_result.questionnaire_results:
filtered_question_results = []
for index, question_result in enumerate(questionnaire_result.question_results):
# filter out if there are no more questions or the next question is also a heading question
if isinstance(question_result, HeadingResult):
if index == len(questionnaire_result.question_results) - 1 or isinstance(questionnaire_result.question_results[index + 1], HeadingResult):
continue
filtered_question_results.append(question_result)
questionnaire_result.question_results = filtered_question_results
# remove empty questionnaire_results and contribution_results
for contribution_result in course_result.contribution_results:
contribution_result.questionnaire_results = [questionnaire_result for questionnaire_result in contribution_result.questionnaire_results if questionnaire_result.question_results]
course_result.contribution_results = [contribution_result for contribution_result in course_result.contribution_results if contribution_result.questionnaire_results]
add_warnings(course, course_result)
# split course_result into different lists
course_questionnaire_results_top = []
course_questionnaire_results_bottom = []
contributor_contribution_results = []
for contribution_result in course_result.contribution_results:
if contribution_result.contributor is None:
for questionnaire_result in contribution_result.questionnaire_results:
if questionnaire_result.questionnaire.is_below_contributors:
course_questionnaire_results_bottom.append(questionnaire_result)
else:
course_questionnaire_results_top.append(questionnaire_result)
else:
contributor_contribution_results.append(contribution_result)
if not contributor_contribution_results:
course_questionnaire_results_top += course_questionnaire_results_bottom
course_questionnaire_results_bottom = []
course.distribution = calculate_average_distribution(course)
course.avg_grade = distribution_to_grade(course.distribution)
template_data = dict(
course=course,
course_questionnaire_results_top=course_questionnaire_results_top,
course_questionnaire_results_bottom=course_questionnaire_results_bottom,
contributor_contribution_results=contributor_contribution_results,
reviewer=request.user.is_reviewer,
contributor=course.is_user_contributor_or_delegate(request.user),
can_download_grades=request.user.can_download_grades,
public_view=public_view)
return render(request, "results_course_detail.html", template_data)
def evaluation_detail(request, semester_id, evaluation_id):
semester = get_object_or_404(Semester, id=semester_id)
evaluation = get_object_or_404(semester.evaluations, id=evaluation_id, course__semester=semester)
if not evaluation.can_results_page_be_seen_by(request.user):
raise PermissionDenied
evaluation_result = collect_results(evaluation)
if request.user.is_reviewer:
view = request.GET.get('view', 'public') # if parameter is not given, show public view.
else:
view = request.GET.get('view', 'full') # if parameter is not given, show own view.
if view not in ['public', 'full', 'export']:
view = 'public'
view_as_user = request.user
if view == 'export' and request.user.is_staff:
view_as_user = UserProfile.objects.get(id=int(request.GET.get('contributor_id', request.user.id)))
represented_users = [view_as_user]
if view != 'export':
represented_users += list(view_as_user.represented_users.all())
# redirect to non-public view if there is none because the results have not been published
if not evaluation.can_publish_rating_results and view == 'public':
view = 'full'
# remove text answers if the user may not see them
for questionnaire_result in evaluation_result.questionnaire_results:
for question_result in questionnaire_result.question_results:
if isinstance(question_result, TextResult):
question_result.answers = [answer for answer in question_result.answers if can_textanswer_be_seen_by(view_as_user, represented_users, answer, view)]
# remove empty TextResults
questionnaire_result.question_results = [result for result in questionnaire_result.question_results if not isinstance(result, TextResult) or len(result.answers) > 0]
# filter empty headings
for questionnaire_result in evaluation_result.questionnaire_results:
filtered_question_results = []
for index, question_result in enumerate(questionnaire_result.question_results):
# filter out if there are no more questions or the next question is also a heading question
if isinstance(question_result, HeadingResult):
if index == len(questionnaire_result.question_results) - 1 or isinstance(questionnaire_result.question_results[index + 1], HeadingResult):
continue
filtered_question_results.append(question_result)
questionnaire_result.question_results = filtered_question_results
# remove empty questionnaire_results and contribution_results
for contribution_result in evaluation_result.contribution_results:
contribution_result.questionnaire_results = [questionnaire_result for questionnaire_result in contribution_result.questionnaire_results if questionnaire_result.question_results]
evaluation_result.contribution_results = [contribution_result for contribution_result in evaluation_result.contribution_results if contribution_result.questionnaire_results]
add_warnings(evaluation, evaluation_result)
# split evaluation_result into different lists
general_questionnaire_results_top = []
general_questionnaire_results_bottom = []
contributor_contribution_results = []
for contribution_result in evaluation_result.contribution_results:
if contribution_result.contributor is None:
for questionnaire_result in contribution_result.questionnaire_results:
if questionnaire_result.questionnaire.is_below_contributors:
general_questionnaire_results_bottom.append(questionnaire_result)
else:
general_questionnaire_results_top.append(questionnaire_result)
elif view != 'export' or view_as_user.id == contribution_result.contributor.id:
contributor_contribution_results.append(contribution_result)
if not contributor_contribution_results:
general_questionnaire_results_top += general_questionnaire_results_bottom
general_questionnaire_results_bottom = []
course_evaluations = []
if evaluation.course.evaluations.count() > 1:
course_evaluations = [evaluation for evaluation in evaluation.course.evaluations.filter(state="published") if evaluation.can_be_seen_by(request.user)]
if request.user.is_reviewer:
course_evaluations += evaluation.course.evaluations.filter(state__in=['in_evaluation', 'evaluated', 'reviewed'])
course_evaluations = get_evaluations_with_course_result_attributes(course_evaluations)
for course_evaluation in course_evaluations:
if course_evaluation.is_single_result:
course_evaluation.single_result_rating_result = get_single_result_rating_result(course_evaluation)
else:
course_evaluation.distribution = calculate_average_distribution(course_evaluation)
course_evaluation.avg_grade = distribution_to_grade(course_evaluation.distribution)
other_contributors = []
if view == 'export':
other_contributors = [contribution_result.contributor for contribution_result in evaluation_result.contribution_results if contribution_result.contributor not in [None, view_as_user]]
# if the evaluation is not published, the rendered results are not cached, so we need to attach distribution
# information for rendering the distribution bar
if evaluation.state != 'published':
evaluation = get_evaluations_with_prefetched_data([evaluation])[0]
template_data = dict(
evaluation=evaluation,
course=evaluation.course,
course_evaluations=course_evaluations,
general_questionnaire_results_top=general_questionnaire_results_top,
general_questionnaire_results_bottom=general_questionnaire_results_bottom,
contributor_contribution_results=contributor_contribution_results,
is_reviewer=view_as_user.is_reviewer,
is_contributor=evaluation.is_user_contributor(view_as_user),
is_responsible_or_contributor_or_delegate=evaluation.is_user_responsible_or_contributor_or_delegate(view_as_user),
can_download_grades=view_as_user.can_download_grades,
view=view,
view_as_user=view_as_user,
other_contributors=other_contributors,
)
return render(request, "results_evaluation_detail.html", template_data)
def index(request):
query = (Evaluation.objects
.annotate(participates_in=Exists(Evaluation.objects.filter(id=OuterRef('id'), participants=request.user)))
.annotate(voted_for=Exists(Evaluation.objects.filter(id=OuterRef('id'), voters=request.user)))
.filter(~Q(state="new"), course__evaluations__participants=request.user)
.exclude(state="new")
.prefetch_related(
'course', 'course__semester', 'course__grade_documents', 'course__type',
'course__evaluations', 'course__responsibles', 'course__degrees',
)
.distinct()
)
query = Evaluation.annotate_with_participant_and_voter_counts(query)
evaluations = [evaluation for evaluation in query if evaluation.can_be_seen_by(request.user)]
inner_evaluation_ids = [inner_evaluation.id for evaluation in evaluations for inner_evaluation in evaluation.course.evaluations.all()]
inner_evaluation_query = Evaluation.objects.filter(pk__in=inner_evaluation_ids)
inner_evaluation_query = Evaluation.annotate_with_participant_and_voter_counts(inner_evaluation_query)
evaluations_by_id = {evaluation['id']: evaluation for evaluation in inner_evaluation_query.values()}
for evaluation in evaluations:
for inner_evaluation in evaluation.course.evaluations.all():
inner_evaluation.num_voters = evaluations_by_id[inner_evaluation.id]['num_voters']
inner_evaluation.num_participants = evaluations_by_id[inner_evaluation.id]['num_participants']
for evaluation in evaluations:
if evaluation.state == "published":
if not evaluation.is_single_result:
evaluation.distribution = calculate_average_distribution(evaluation)
else:
evaluation.single_result_rating_result = get_single_result_rating_result(evaluation)
evaluation.distribution = normalized_distribution(evaluation.single_result_rating_result.counts)
evaluation.avg_grade = distribution_to_grade(evaluation.distribution)
evaluations = get_evaluations_with_course_result_attributes(evaluations)
# evaluations must be sorted for regrouping them in the template
evaluations.sort(key=lambda evaluation: (evaluation.course.name, evaluation.name))
semesters = Semester.objects.all()
semester_list = [dict(
semester_name=semester.name,
id=semester.id,
results_are_archived=semester.results_are_archived,
grade_documents_are_deleted=semester.grade_documents_are_deleted,
evaluations=[evaluation for evaluation in evaluations if evaluation.course.semester_id == semester.id]
) for semester in semesters]
unfinished_evaluations_query = (
Evaluation.objects
.filter(participants=request.user, state__in=['prepared', 'editor_approved', 'approved', 'in_evaluation'])
.exclude(voters=request.user)
.prefetch_related('course__responsibles', 'course__type', 'course__semester')
)
unfinished_evaluations_query = Evaluation.annotate_with_participant_and_voter_counts(unfinished_evaluations_query)
unfinished_evaluations = list(unfinished_evaluations_query)
# available evaluations come first, ordered by time left for evaluation and the name
# evaluations in other (visible) states follow by name
def sorter(evaluation):
return (
evaluation.state != 'in_evaluation',
evaluation.vote_end_date if evaluation.state == 'in_evaluation' else None,
evaluation.full_name
)
unfinished_evaluations.sort(key=sorter)
template_data = dict(
semester_list=semester_list,
can_download_grades=request.user.can_download_grades,
unfinished_evaluations=unfinished_evaluations,
evaluation_end_warning_period=settings.EVALUATION_END_WARNING_PERIOD,
)
return render(request, "student_index.html", template_data)
def export(self, response, course_types_list, include_not_enough_voters=False, include_unpublished=False):
self.workbook = xlwt.Workbook()
self.init_styles(self.workbook)
counter = 1
course_results_exist = False
for course_types in course_types_list:
self.sheet = self.workbook.add_sheet("Sheet " + str(counter))
counter += 1
self.row = 0
self.col = 0
evaluations_with_results = list()
evaluation_states = ['published']
if include_unpublished:
evaluation_states.extend(['evaluated', 'reviewed'])
used_questionnaires = set()
for evaluation in self.semester.evaluations.filter(state__in=evaluation_states, course__type__in=course_types).all():
if evaluation.is_single_result:
continue
if not evaluation.can_publish_rating_results and not include_not_enough_voters:
continue
results = OrderedDict()
for questionnaire_result in collect_results(evaluation).questionnaire_results:
if all(not question_result.question.is_rating_question or question_result.counts is None for question_result in questionnaire_result.question_results):
continue
results.setdefault(questionnaire_result.questionnaire.id, []).extend(questionnaire_result.question_results)
used_questionnaires.add(questionnaire_result.questionnaire)
evaluation.course_evaluations_count = evaluation.course.evaluations.count()
if evaluation.course_evaluations_count > 1:
course_results_exist = True
evaluation.weight_percentage = int((evaluation.weight / sum(evaluation.weight for evaluation in evaluation.course.evaluations.all())) * 100)
evaluation.course.avg_grade = distribution_to_grade(calculate_average_course_distribution(evaluation.course))
evaluations_with_results.append((evaluation, results))
evaluations_with_results.sort(key=lambda cr: (cr[0].course.type.order, cr[0].full_name))
used_questionnaires = sorted(used_questionnaires)
course_type_names = [ct.name for ct in CourseType.objects.filter(pk__in=course_types)]
writec(self, _("Evaluation {0}\n\n{1}").format(self.semester.name, ", ".join(course_type_names)), "headline")
for evaluation, results in evaluations_with_results:
writec(self, evaluation.full_name, "evaluation")
writen(self, _("Course Degrees"), "bold")
for evaluation, results in evaluations_with_results:
writec(self, "\n".join([d.name for d in evaluation.course.degrees.all()]), "degree")
writen(self, _("Course Type"), "bold")
for evaluation, results in evaluations_with_results:
writec(self, evaluation.course.type.name, "border_left_right")
writen(self)
for evaluation, results in evaluations_with_results:
self.write_empty_cell_with_borders()
for questionnaire in used_questionnaires:
writen(self, questionnaire.name, "bold")
for evaluation, results in evaluations_with_results:
self.write_empty_cell_with_borders()
filtered_questions = self.filter_text_and_heading_questions(questionnaire.questions.all())
for question in filtered_questions:
if question.is_heading_question:
writen(self, question.text, "italic")
else:
writen(self, question.text)
for evaluation, results in evaluations_with_results:
if questionnaire.id not in results or question.is_heading_question:
self.write_empty_cell_with_borders()
continue
qn_results = results[questionnaire.id]
values = []
count_sum = 0
approval_count = 0
for grade_result in qn_results:
if grade_result.question.id == question.id:
if grade_result.has_answers:
values.append(grade_result.average * grade_result.count_sum)
count_sum += grade_result.count_sum
if grade_result.question.is_yes_no_question:
approval_count += grade_result.approval_count
if values:
avg = sum(values) / count_sum
if question.is_yes_no_question:
percent_approval = approval_count / count_sum if count_sum > 0 else 0
writec(self, "{:.0%}".format(percent_approval), self.grade_to_style(avg))
else:
writec(self, avg, self.grade_to_style(avg))
else:
self.write_empty_cell_with_borders()
writen(self)
for evaluation, results in evaluations_with_results:
self.write_empty_cell_with_borders()
writen(self, _("Overall Average Grade"), "bold")
for evaluation, results in evaluations_with_results:
avg = distribution_to_grade(calculate_average_distribution(evaluation))
if avg:
writec(self, avg, self.grade_to_style(avg))
else:
self.write_empty_cell_with_borders()
writen(self, _("Total voters/Total participants"), "bold")
for evaluation, results in evaluations_with_results:
writec(self, "{}/{}".format(evaluation.num_voters, evaluation.num_participants), "total_voters")
writen(self, _("Evaluation rate"), "bold")
for evaluation, results in evaluations_with_results:
# round down like in progress bar
percentage_participants = int((evaluation.num_voters / evaluation.num_participants) * 100) if evaluation.num_participants > 0 else 0
writec(self, "{}%".format(percentage_participants), "evaluation_rate")
if course_results_exist:
writen(self)
for evaluation, results in evaluations_with_results:
if evaluation.course_evaluations_count > 1:
self.write_empty_cell_with_borders()
else:
self.write_empty_cell()
writen(self, _("Evaluation weight"), "bold")
for evaluation, results in evaluations_with_results:
if evaluation.course_evaluations_count > 1:
writec(self, "{}%".format(evaluation.weight_percentage), "evaluation_weight")
else:
self.write_empty_cell()
writen(self, _("Course Grade"), "bold")
for evaluation, results in evaluations_with_results:
if evaluation.course_evaluations_count > 1:
if evaluation.course.avg_grade:
writec(self, evaluation.course.avg_grade, self.grade_to_style(evaluation.course.avg_grade))
else:
self.write_empty_cell_with_borders()
else:
self.write_empty_cell()
writen(self)
for evaluation, results in evaluations_with_results:
if evaluation.course_evaluations_count > 1:
writec(self, None, "border_top")
else:
self.write_empty_cell()
self.workbook.save(response)