def test_trr_count(self):
officer_1 = OfficerFactory()
officer_2 = OfficerFactory()
TRRFactory.create_batch(2, officer=officer_1)
officer_cache_manager.build_cached_columns()
officer_1.refresh_from_db()
officer_2.refresh_from_db()
expect(officer_1.trr_count).to.eq(2)
expect(officer_2.trr_count).to.eq(0)
def test_latest_year_percentile(self):
officer1 = OfficerFactory(id=1, appointed_date=date(1990, 3, 14))
officer2 = OfficerFactory(id=2,
appointed_date=date(1990, 3, 14),
resignation_date=date(2014, 7, 1))
officer3 = OfficerFactory(id=3, appointed_date=date(1990, 3, 14))
officer4 = OfficerFactory(id=4,
appointed_date=date(1990, 3, 14),
resignation_date=date(2010, 7, 1))
# officer1 have all data
OfficerAllegationFactory.create_batch(
2,
officer=officer1,
allegation__incident_date=datetime(2013, 12, 31, tzinfo=pytz.utc),
)
OfficerAllegationFactory.create_batch(
3,
officer=officer1,
allegation__incident_date=datetime(2015, 7, 2, tzinfo=pytz.utc),
allegation__is_officer_complaint=True)
OfficerAllegationFactory.create_batch(
4,
officer=officer1,
allegation__incident_date=datetime(2015, 7, 2, tzinfo=pytz.utc),
allegation__is_officer_complaint=False)
TRRFactory.create_batch(2,
officer=officer1,
trr_datetime=datetime(2015,
2,
1,
tzinfo=pytz.utc))
AwardFactory(officer=officer1,
award_type='Complimentary Letter',
start_date=datetime(2013, 1, 1))
AwardFactory.create_batch(3,
officer=officer1,
award_type='Honorable Mention',
start_date=datetime(2015, 1, 1))
# officer2 don't have trr
OfficerAllegationFactory(
officer=officer2,
allegation__incident_date=datetime(2013, 12, 31, tzinfo=pytz.utc),
)
OfficerAllegationFactory(officer=officer2,
allegation__incident_date=datetime(
2014, 7, 2, tzinfo=pytz.utc),
allegation__is_officer_complaint=True)
OfficerAllegationFactory(officer=officer2,
allegation__incident_date=datetime(
2014, 7, 2, tzinfo=pytz.utc),
allegation__is_officer_complaint=False)
AwardFactory(officer=officer2,
award_type='Complimentary Letter',
start_date=datetime(2013, 1, 1))
AwardFactory.create_batch(3,
officer=officer2,
award_type='Honorable Mention',
start_date=datetime(2014, 1, 1))
# officer3 don't have allegation in ALLEGATION_MIN - ALLEGATION_MAX
OfficerAllegationFactory.create_batch(
2,
officer=officer3,
allegation__incident_date=datetime(2015, 7, 2, tzinfo=pytz.utc),
allegation__is_officer_complaint=True)
OfficerAllegationFactory.create_batch(
3,
officer=officer3,
allegation__incident_date=datetime(2015, 7, 2, tzinfo=pytz.utc),
allegation__is_officer_complaint=False)
TRRFactory.create_batch(3,
officer=officer3,
trr_datetime=datetime(2015,
2,
1,
tzinfo=pytz.utc))
# officer4 have all data but is out of data range
OfficerAllegationFactory.create_batch(
2,
officer=officer4,
allegation__incident_date=datetime(2009, 12, 31, tzinfo=pytz.utc),
)
OfficerAllegationFactory.create_batch(
3,
officer=officer4,
allegation__incident_date=datetime(2009, 7, 2, tzinfo=pytz.utc),
allegation__is_officer_complaint=True)
OfficerAllegationFactory.create_batch(
4,
officer=officer4,
allegation__incident_date=datetime(2009, 7, 2, tzinfo=pytz.utc),
allegation__is_officer_complaint=False)
TRRFactory.create_batch(2,
officer=officer4,
trr_datetime=datetime(2009,
2,
1,
tzinfo=pytz.utc))
expected_dict = {
1: {
'officer_id': 1,
'year': 2017,
'metric_allegation': 3.0,
'metric_allegation_civilian': 2.0,
'metric_allegation_internal': 1.0,
'metric_trr': 0.6667,
'metric_honorable_mention': 1.0,
'percentile_allegation': 66.6667,
'percentile_allegation_civilian': 66.6667,
'percentile_allegation_internal': 66.6667,
'percentile_trr': 33.3333,
'percentile_honorable_mention': 33.3333,
},
2: {
'officer_id': 2,
'year': 2014,
'metric_allegation': 2.0055,
'metric_allegation_civilian': 1.337,
'metric_allegation_internal': 0.6685,
'metric_trr': 0.0,
'metric_honorable_mention': 2.0055,
'percentile_allegation': 66.6667,
'percentile_allegation_civilian': 66.6667,
'percentile_allegation_internal': 66.6667,
'percentile_trr': 0.0,
'percentile_honorable_mention': 66.6667
},
3: {
'officer_id': 3,
'year': 2017,
'metric_allegation': 1.6667,
'metric_allegation_civilian': 1.0,
'metric_allegation_internal': 0.6667,
'metric_trr': 1.0,
'metric_honorable_mention': 0.0,
'percentile_allegation': 0.0,
'percentile_allegation_civilian': 0.0,
'percentile_allegation_internal': 0.0,
'percentile_trr': 66.6667,
'percentile_honorable_mention': 0.0
}
}
officers = officer_percentile.latest_year_percentile()
expect(officers).to.have.length(3)
for officer in officers:
validate_object(officer, expected_dict[officer.id])
def test_top_percentile_not_enough_service_year(self):
officer1 = OfficerFactory(id=1, appointed_date=date(1990, 3, 14))
officer2 = OfficerFactory(id=2,
appointed_date=date(1990, 3, 14),
resignation_date=date(2014, 5, 1))
officer3 = OfficerFactory(id=3, appointed_date=date(2013, 3, 14))
officer4 = OfficerFactory(id=4,
appointed_date=date(1990, 3, 14),
resignation_date=date(2015, 5, 1))
# officer1 have all data
OfficerAllegationFactory.create_batch(
2,
officer=officer1,
allegation__incident_date=datetime(2013, 12, 31, tzinfo=pytz.utc),
)
OfficerAllegationFactory.create_batch(
3,
officer=officer1,
allegation__incident_date=datetime(2014, 7, 2, tzinfo=pytz.utc),
allegation__is_officer_complaint=True)
OfficerAllegationFactory.create_batch(
4,
officer=officer1,
allegation__incident_date=datetime(2014, 7, 2, tzinfo=pytz.utc),
allegation__is_officer_complaint=False)
TRRFactory.create_batch(2,
officer=officer1,
trr_datetime=datetime(2015,
2,
1,
tzinfo=pytz.utc))
# officer2 don't have trr
OfficerAllegationFactory(
officer=officer2,
allegation__incident_date=datetime(2013, 12, 31, tzinfo=pytz.utc),
)
OfficerAllegationFactory(officer=officer2,
allegation__incident_date=datetime(
2014, 2, 2, tzinfo=pytz.utc),
allegation__is_officer_complaint=True)
OfficerAllegationFactory(officer=officer2,
allegation__incident_date=datetime(
2014, 3, 2, tzinfo=pytz.utc),
allegation__is_officer_complaint=False)
# officer3 don't have allegation in ALLEGATION_MIN - ALLEGATION_MAX
OfficerAllegationFactory.create_batch(
2,
officer=officer3,
allegation__incident_date=datetime(2014, 7, 2, tzinfo=pytz.utc),
allegation__is_officer_complaint=True)
OfficerAllegationFactory.create_batch(
3,
officer=officer3,
allegation__incident_date=datetime(2014, 7, 2, tzinfo=pytz.utc),
allegation__is_officer_complaint=False)
TRRFactory.create_batch(3,
officer=officer3,
trr_datetime=datetime(2015,
2,
1,
tzinfo=pytz.utc))
# officer4 don't have allegation in INTERNAL_CIVILIAN_ALLEGATION year range
OfficerAllegationFactory.create_batch(
5,
officer=officer4,
allegation__incident_date=datetime(2013, 12, 31, tzinfo=pytz.utc),
)
TRRFactory.create_batch(6,
officer=officer4,
trr_datetime=datetime(2015,
2,
1,
tzinfo=pytz.utc))
expected_dict = {
1: {
'officer_id': 1,
'year': 2016,
'metric_allegation': 2,
'metric_allegation_civilian': 4,
'metric_allegation_internal': 3,
'metric_trr': 2,
'percentile_allegation': 33.3333,
'percentile_allegation_civilian': 66.6667,
'percentile_allegation_internal': 66.6667,
'percentile_trr': 0.0
},
2: {
'officer_id': 2,
'year': 2016,
'metric_allegation': 1,
'metric_allegation_civilian': None,
'metric_allegation_internal': None,
'metric_trr': None,
'percentile_allegation': 0.0,
'percentile_allegation_civilian': None,
'percentile_allegation_internal': None,
'percentile_trr': None
},
3: {
'officer_id': 3,
'year': 2016,
'metric_allegation': None,
'metric_allegation_civilian': 3,
'metric_allegation_internal': 2,
'metric_trr': 3,
'percentile_allegation': None,
'percentile_allegation_civilian': 33.3333,
'percentile_allegation_internal': 33.3333,
'percentile_trr': 50.0
},
4: {
'officer_id': 4,
'year': 2016,
'metric_allegation': 5,
'metric_allegation_civilian': 0.0,
'metric_allegation_internal': 0.0,
'metric_trr': None,
'percentile_allegation': 66.6667,
'percentile_allegation_civilian': 0.0,
'percentile_allegation_internal': 0.0,
'percentile_trr': None
}
}
officers = officer_percentile.top_percentile(2016)
for officer in officers:
validate_object(officer, expected_dict[officer.id])
def test_top_percentile_with_types(self):
officer1 = OfficerFactory(id=1, appointed_date=date(1990, 3, 14))
officer2 = OfficerFactory(id=2, appointed_date=date(1990, 3, 14))
officer3 = OfficerFactory(id=3, appointed_date=date(1990, 3, 14))
officer4 = OfficerFactory(id=4, appointed_date=date(1990, 3, 14))
# officer1 have all data
OfficerAllegationFactory.create_batch(
2,
officer=officer1,
allegation__incident_date=datetime(2013, 12, 31, tzinfo=pytz.utc),
)
OfficerAllegationFactory.create_batch(
3,
officer=officer1,
allegation__incident_date=datetime(2015, 7, 2, tzinfo=pytz.utc),
allegation__is_officer_complaint=True)
OfficerAllegationFactory.create_batch(
4,
officer=officer1,
allegation__incident_date=datetime(2015, 7, 2, tzinfo=pytz.utc),
allegation__is_officer_complaint=False)
TRRFactory.create_batch(2,
officer=officer1,
trr_datetime=datetime(2015,
2,
1,
tzinfo=pytz.utc))
# officer2 don't have trr
OfficerAllegationFactory(
officer=officer2,
allegation__incident_date=datetime(2013, 12, 31, tzinfo=pytz.utc),
)
OfficerAllegationFactory(officer=officer2,
allegation__incident_date=datetime(
2015, 7, 2, tzinfo=pytz.utc),
allegation__is_officer_complaint=True)
OfficerAllegationFactory(officer=officer2,
allegation__incident_date=datetime(
2015, 7, 2, tzinfo=pytz.utc),
allegation__is_officer_complaint=False)
# officer3 don't have allegation in ALLEGATION_MIN - ALLEGATION_MAX
OfficerAllegationFactory.create_batch(
2,
officer=officer3,
allegation__incident_date=datetime(2015, 7, 2, tzinfo=pytz.utc),
allegation__is_officer_complaint=True)
OfficerAllegationFactory.create_batch(
3,
officer=officer3,
allegation__incident_date=datetime(2015, 7, 2, tzinfo=pytz.utc),
allegation__is_officer_complaint=False)
TRRFactory.create_batch(3,
officer=officer3,
trr_datetime=datetime(2015,
2,
1,
tzinfo=pytz.utc))
# officer4 don't have allegation in INTERNAL_CIVILIAN_ALLEGATION year range
OfficerAllegationFactory.create_batch(
5,
officer=officer4,
allegation__incident_date=datetime(2013, 12, 31, tzinfo=pytz.utc),
)
TRRFactory.create_batch(6,
officer=officer4,
trr_datetime=datetime(2015,
2,
1,
tzinfo=pytz.utc))
expected_dict = {
1: {
'officer_id': 1,
'year': 2016,
'metric_allegation_civilian': 4,
'metric_allegation_internal': 3,
'metric_trr': 2,
'percentile_allegation': None,
'percentile_allegation_civilian': 75.0,
'percentile_allegation_internal': 75.0,
'percentile_trr': 25.0
},
2: {
'officer_id': 2,
'year': 2016,
'metric_allegation_civilian': 1,
'metric_allegation_internal': 1,
'metric_trr': 0.0,
'percentile_allegation': None,
'percentile_allegation_civilian': 25.0,
'percentile_allegation_internal': 25.0,
'percentile_trr': 0.0
},
3: {
'officer_id': 3,
'year': 2016,
'metric_allegation_civilian': 3,
'metric_allegation_internal': 2,
'metric_trr': 3,
'percentile_allegation': None,
'percentile_allegation_civilian': 50.0,
'percentile_allegation_internal': 50.0,
'percentile_trr': 50.0
},
4: {
'officer_id': 4,
'year': 2016,
'metric_allegation_civilian': 0.0,
'metric_allegation_internal': 0.0,
'metric_trr': 6,
'percentile_allegation': None,
'percentile_allegation_civilian': 0.0,
'percentile_allegation_internal': 0.0,
'percentile_trr': 75.0
}
}
visual_token_percentile_groups = [
PERCENTILE_ALLEGATION_INTERNAL_CIVILIAN_GROUP, PERCENTILE_TRR_GROUP
]
officers = officer_percentile.top_percentile(
2016, percentile_groups=visual_token_percentile_groups)
for officer in officers:
validate_object(officer, expected_dict[officer.id])
def test_top_percentile(self):
officer1 = OfficerFactory(id=1, appointed_date=date(1990, 3, 14))
officer2 = OfficerFactory(id=2, appointed_date=date(1990, 3, 14))
officer3 = OfficerFactory(id=3, appointed_date=date(1990, 3, 14))
# officer1 have all data
OfficerAllegationFactory.create_batch(
2,
officer=officer1,
allegation__incident_date=datetime(2013, 12, 31, tzinfo=pytz.utc),
)
OfficerAllegationFactory.create_batch(
3,
officer=officer1,
allegation__incident_date=datetime(2015, 7, 2, tzinfo=pytz.utc),
allegation__is_officer_complaint=True)
OfficerAllegationFactory.create_batch(
4,
officer=officer1,
allegation__incident_date=datetime(2015, 7, 2, tzinfo=pytz.utc),
allegation__is_officer_complaint=False)
TRRFactory.create_batch(2,
officer=officer1,
trr_datetime=datetime(2015,
2,
1,
tzinfo=pytz.utc))
# officer2 don't have trr
OfficerAllegationFactory(
officer=officer2,
allegation__incident_date=datetime(2013, 12, 31, tzinfo=pytz.utc),
)
OfficerAllegationFactory(officer=officer2,
allegation__incident_date=datetime(
2015, 7, 2, tzinfo=pytz.utc),
allegation__is_officer_complaint=True)
OfficerAllegationFactory(officer=officer2,
allegation__incident_date=datetime(
2015, 7, 2, tzinfo=pytz.utc),
allegation__is_officer_complaint=False)
# officer3 don't have allegation in ALLEGATION_MIN - ALLEGATION_MAX
OfficerAllegationFactory.create_batch(
2,
officer=officer3,
allegation__incident_date=datetime(2015, 7, 2, tzinfo=pytz.utc),
allegation__is_officer_complaint=True)
OfficerAllegationFactory.create_batch(
3,
officer=officer3,
allegation__incident_date=datetime(2015, 7, 2, tzinfo=pytz.utc),
allegation__is_officer_complaint=False)
TRRFactory.create_batch(3,
officer=officer3,
trr_datetime=datetime(2015,
2,
1,
tzinfo=pytz.utc))
expected_dict = {
1: {
'officer_id': 1,
'year': 2016,
'metric_allegation': 2,
'metric_allegation_civilian': 4,
'metric_allegation_internal': 3,
'metric_trr': 2,
'percentile_allegation': 66.6667,
'percentile_allegation_civilian': 66.6667,
'percentile_allegation_internal': 66.6667,
'percentile_trr': 33.3333
},
2: {
'officer_id': 2,
'year': 2016,
'metric_allegation': 1,
'metric_allegation_civilian': 1,
'metric_allegation_internal': 1,
'metric_trr': 0.0,
'percentile_allegation': 33.3333,
'percentile_allegation_civilian': 0.0000,
'percentile_allegation_internal': 0.0000,
'percentile_trr': 0.0
},
3: {
'officer_id': 3,
'year': 2016,
'metric_allegation': 0.0,
'metric_allegation_civilian': 3,
'metric_allegation_internal': 2,
'metric_trr': 3,
'percentile_allegation': 0.0,
'percentile_allegation_civilian': 33.3333,
'percentile_allegation_internal': 33.3333,
'percentile_trr': 66.6667,
}
}
officers = officer_percentile.top_percentile(2016)
for officer in officers:
validate_object(officer, expected_dict[officer.id])
