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edx-platform/lms/djangoapps/instructor_analytics/tests/test_distributions.py
2015-02-04 09:09:14 -05:00

117 lines
5.0 KiB
Python

""" Tests for analytics.distributions """
from django.test import TestCase
from nose.tools import raises
from student.models import CourseEnrollment
from student.tests.factories import UserFactory
from opaque_keys.edx.locations import SlashSeparatedCourseKey
from instructor_analytics.distributions import profile_distribution, AVAILABLE_PROFILE_FEATURES
class TestAnalyticsDistributions(TestCase):
'''Test analytics distribution gathering.'''
def setUp(self):
super(TestAnalyticsDistributions, self).setUp()
self.course_id = SlashSeparatedCourseKey('robot', 'course', 'id')
self.users = [UserFactory(
profile__gender=['m', 'f', 'o'][i % 3],
profile__level_of_education=['a', 'hs', 'el'][i % 3],
profile__year_of_birth=i + 1930
) for i in xrange(30)]
self.ces = [CourseEnrollment.enroll(user, self.course_id)
for user in self.users]
@raises(ValueError)
def test_profile_distribution_bad_feature(self):
feature = 'robot-not-a-real-feature'
self.assertNotIn(feature, AVAILABLE_PROFILE_FEATURES)
profile_distribution(self.course_id, feature)
def test_profile_distribution_easy_choice(self):
feature = 'gender'
self.assertIn(feature, AVAILABLE_PROFILE_FEATURES)
distribution = profile_distribution(self.course_id, feature)
self.assertEqual(distribution.type, 'EASY_CHOICE')
self.assertEqual(distribution.data['no_data'], 0)
self.assertEqual(distribution.data['m'], len(self.users) / 3)
self.assertEqual(distribution.choices_display_names['m'], 'Male')
def test_profile_distribution_open_choice(self):
feature = 'year_of_birth'
self.assertIn(feature, AVAILABLE_PROFILE_FEATURES)
distribution = profile_distribution(self.course_id, feature)
print distribution
self.assertEqual(distribution.type, 'OPEN_CHOICE')
self.assertTrue(hasattr(distribution, 'choices_display_names'))
self.assertEqual(distribution.choices_display_names, None)
self.assertNotIn('no_data', distribution.data)
self.assertEqual(distribution.data[1930], 1)
def test_gender_count(self):
course_enrollments = CourseEnrollment.objects.filter(
course_id=self.course_id, user__profile__gender='m'
)
distribution = profile_distribution(self.course_id, "gender")
self.assertEqual(distribution.data['m'], len(course_enrollments))
course_enrollments[0].deactivate()
distribution = profile_distribution(self.course_id, "gender")
self.assertEqual(distribution.data['m'], len(course_enrollments) - 1)
def test_level_of_education_count(self):
course_enrollments = CourseEnrollment.objects.filter(
course_id=self.course_id, user__profile__level_of_education='hs'
)
distribution = profile_distribution(self.course_id, "level_of_education")
self.assertEqual(distribution.data['hs'], len(course_enrollments))
course_enrollments[0].deactivate()
distribution = profile_distribution(self.course_id, "level_of_education")
self.assertEqual(distribution.data['hs'], len(course_enrollments) - 1)
class TestAnalyticsDistributionsNoData(TestCase):
'''Test analytics distribution gathering.'''
def setUp(self):
super(TestAnalyticsDistributionsNoData, self).setUp()
self.course_id = SlashSeparatedCourseKey('robot', 'course', 'id')
self.users = [UserFactory(
profile__year_of_birth=i + 1930,
) for i in xrange(5)]
self.nodata_users = [UserFactory(
profile__year_of_birth=None,
profile__gender=[None, ''][i % 2]
) for i in xrange(4)]
self.users += self.nodata_users
self.ces = tuple(CourseEnrollment.enroll(user, self.course_id)
for user in self.users)
def test_profile_distribution_easy_choice_nodata(self):
feature = 'gender'
self.assertIn(feature, AVAILABLE_PROFILE_FEATURES)
distribution = profile_distribution(self.course_id, feature)
print distribution
self.assertEqual(distribution.type, 'EASY_CHOICE')
self.assertTrue(hasattr(distribution, 'choices_display_names'))
self.assertNotEqual(distribution.choices_display_names, None)
self.assertIn('no_data', distribution.data)
self.assertEqual(distribution.data['no_data'], len(self.nodata_users))
def test_profile_distribution_open_choice_nodata(self):
feature = 'year_of_birth'
self.assertIn(feature, AVAILABLE_PROFILE_FEATURES)
distribution = profile_distribution(self.course_id, feature)
print distribution
self.assertEqual(distribution.type, 'OPEN_CHOICE')
self.assertTrue(hasattr(distribution, 'choices_display_names'))
self.assertEqual(distribution.choices_display_names, None)
self.assertIn('no_data', distribution.data)
self.assertEqual(distribution.data['no_data'], len(self.nodata_users))