def testBlindUserAggregation(self):
actual = aggregate_subject_annotations(
self.test_subjects['test_blind_user'],
self.questions,
self.question_type_map,
self.question_main_id)
actual_consensus = {x for x in actual['consensus_species']}
expected_consensus = {'zebra'}
actual_agg_info = actual['aggregation_info']
expected_agg_info = {
'n_species_ids_per_user_max': 1,
'n_species_ids_per_user_median': 1,
'n_users_classified_this_subject': 4,
'n_users_saw_a_species': 3,
'n_users_saw_no_species': 1,
'p_users_saw_a_species': '0.75',
'pielous_evenness_index': '0.00'}
self.assertEqual(expected_agg_info, actual_agg_info)
self.assertEqual(actual_consensus, expected_consensus)
actual_species_aggs = actual['species_aggregations']
expected_spcies_aggs = {'zebra': {
'n_users_identified_this_species': 3,
'p_users_identified_this_species': '1.00',
'question__count_max': '4',
'question__count_median': '1',
'question__count_min': '1',
'question__standing': '0.33'}}
self.assertEqual(actual_species_aggs, expected_spcies_aggs)
def testNotBlankOn50To50(self):
actual = aggregate_subject_annotations(
self.test_subjects['test_not_blank'],
self.questions,
self.question_type_map,
self.question_main_id)
actual_consensus = {x for x in actual['consensus_species']}
self.assertNotIn('blank', actual_consensus)
def testConsensusFirstOnTie2(self):
actual = aggregate_subject_annotations(
self.test_subjects['test_tie_eland'],
self.questions,
self.question_type_map,
self.question_main_id)
actual_consensus = {x for x in actual['consensus_species']}
self.assertIn('eland', actual_consensus)
self.assertEqual(1, len(actual_consensus))
def testIsBlank(self):
actual = aggregate_subject_annotations(
self.test_subjects['test_blank'],
self.questions,
self.question_type_map,
self.question_main_id)
actual_consensus = {x for x in actual['consensus_species']}
self.assertIn('blank', actual_consensus)
self.assertEqual(1, len(actual_consensus))
def testCountAgg(self):
actual = aggregate_subject_annotations(
self.test_subjects['test_count_10'],
self.questions,
self.question_type_map,
self.question_main_id)
actual_species_aggs = actual['species_aggregations']
expected_spcies_aggs = {'zebra': {
'n_users_identified_this_species': 4,
'p_users_identified_this_species': '1.00',
'question__count_max': '11-50',
'question__count_median': '10',
'question__count_min': '9',
'question__standing': '0.00'}}
self.assertEqual(actual_species_aggs, expected_spcies_aggs)
def testProportionAggPartial(self):
actual = aggregate_subject_annotations(
self.test_subjects['test_prop_025'],
self.questions,
self.question_type_map,
self.question_main_id)
actual_species_aggs = actual['species_aggregations']
expected_spcies_aggs = {'zebra': {
'n_users_identified_this_species': 4,
'p_users_identified_this_species': '1.00',
'question__count_max': '6',
'question__count_median': '4',
'question__count_min': '1',
'question__standing': '0.25'}}
self.assertEqual(actual_species_aggs, expected_spcies_aggs)
def testStandardAggregation(self):
actual = aggregate_subject_annotations(
self.test_subjects['test_standard'],
self.questions,
self.question_type_map,
self.question_main_id)
actual_consensus = actual['consensus_species'][0]
actual_agg_info = actual['aggregation_info']
expected_consensus = 'zebra'
expected_agg_info = {
'n_species_ids_per_user_max': 1,
'n_species_ids_per_user_median': 1,
'n_users_classified_this_subject': 3,
'n_users_saw_a_species': 3,
'n_users_saw_no_species': 0,
'p_users_saw_a_species': '1.00',
'pielous_evenness_index': '0.00'}
self.assertEqual(expected_agg_info, actual_agg_info)
self.assertEqual(actual_consensus, expected_consensus)
def testMulti2SpeciesAggregation(self):
actual = aggregate_subject_annotations(
self.test_subjects['test_multi2'],
self.questions,
self.question_type_map,
self.question_main_id)
actual_consensus = {x for x in actual['consensus_species']}
expected_consensus = {'zebra', 'elephant'}
actual_agg_info = actual['aggregation_info']
expected_agg_info = {
'n_species_ids_per_user_max': 3,
'n_species_ids_per_user_median': 2,
'n_users_classified_this_subject': 3,
'n_users_saw_a_species': 3,
'n_users_saw_no_species': 0,
'p_users_saw_a_species': '1.00',
'pielous_evenness_index': '0.91'}
self.assertEqual(expected_agg_info, actual_agg_info)
self.assertEqual(actual_consensus, expected_consensus)
def testMinorityAgg(self):
actual = aggregate_subject_annotations(
self.test_subjects['test_minority'],
self.questions,
self.question_type_map,
self.question_main_id)
actual_species_aggs = actual['species_aggregations']
expected_spcies_aggs = {'zebra': {
'n_users_identified_this_species': 2,
'p_users_identified_this_species': '0.67',
'question__count_max': '2',
'question__count_median': '2',
'question__count_min': '1',
'question__standing': '0.00'},
'eland': {
'n_users_identified_this_species': 1,
'p_users_identified_this_species': '0.33',
'question__count_max': '2',
'question__count_median': '2',
'question__count_min': '2',
'question__standing': '0.00'}}
self.assertEqual(actual_species_aggs, expected_spcies_aggs)
