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)
 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_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_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(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_profile_distribution_bad_feature(self):
     feature = 'robot-not-a-real-feature'
     self.assertNotIn(feature, AVAILABLE_PROFILE_FEATURES)
     with pytest.raises(ValueError):
         profile_distribution(self.course_id, feature)
 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)
Example #9
0
 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)