def assert_update(self,
purge_date,
adherence_schedule_date_start,
adherence_schedule_id,
adherence_cases,
episode_properties=None,
date_today_in_india=None,
output=None):
adherence_cases = [{
"name": adherence_case[0],
"adherence_value": adherence_case[1],
"adherence_source": "enikshay",
"adherence_report_source": "treatment_supervisor"
} for adherence_case in adherence_cases]
episode = self.create_episode_case(
adherence_schedule_date_start,
adherence_schedule_id,
adherence_cases,
extra_properties=episode_properties,
)
updater = EpisodeAdherenceUpdate(self.domain, episode)
updater.purge_date = purge_date
if date_today_in_india is not None:
updater.date_today_in_india = date_today_in_india
return self.assert_properties_equal(output, updater.update_json())
def get_doses(self):
adherence_cases = []
for day, cases in self.get_adherence_cases_dict().iteritems():
adherence_cases.extend(cases)
doses_taken_by_date = EpisodeAdherenceUpdate.calculate_doses_taken_by_day(
[c.to_json() for c in adherence_cases])
return EpisodeAdherenceUpdate.count_doses_taken(doses_taken_by_date)
def test_missed_and_unknown_doses(self):
adherence_cases = [{
"name": str(i),
"adherence_source": "enikshay",
"adherence_value": adherence_value,
"adherence_date": date,
} for i, (adherence_value, date) in enumerate([
# one month
(DOSE_MISSED, datetime.date(2016, 1, 13)),
('unobserved_dose', datetime.date(2016, 1, 15)),
# two weeks
('directly_observed_dose', datetime.date(2016, 1, 17)),
(DOSE_UNKNOWN, datetime.date(2016, 1, 18)),
# one week
('directly_observed_dose', datetime.date(2016, 1, 26)),
# three days
('directly_observed_dose', datetime.date(2016, 1, 29)),
(DOSE_MISSED, datetime.date(2016, 1, 31)),
('', datetime.date(2016, 1, 30)), # blank should be treated as unknown
])]
episode = self.create_episode_case(
adherence_schedule_date_start=datetime.date(2015, 12, 1),
adherence_schedule_id='schedule1',
adherence_cases=adherence_cases,
)
updater = EpisodeAdherenceUpdate(self.domain, episode)
updater.date_today_in_india = datetime.date(2016, 1, 31)
expected = {
'three_day_score_count_taken': 1,
'one_week_score_count_taken': 2,
'two_week_score_count_taken': 3,
'month_score_count_taken': 4,
'three_day_unknown_count': 3 - 2,
'one_week_unknown_count': 7 - 3,
'two_week_unknown_count': 14 - 4,
'month_unknown_count': 30 - 6,
'three_day_missed_count': 1,
'one_week_missed_count': 1,
'two_week_missed_count': 1,
'month_missed_count': 2,
'three_day_unknown_score': 33.33,
'one_week_unknown_score': 57.14,
'two_week_unknown_score': 71.43,
'month_unknown_score': 80.0,
'three_day_missed_score': 33.33,
'one_week_missed_score': 14.29,
'two_week_missed_score': 7.14,
'month_missed_score': 6.67,
}
actual = updater.update_json()
self.assert_properties_equal(expected, actual)
readable_day_names = {
3: 'three_day',
7: 'one_week',
14: 'two_week',
30: 'month',
}
for days, period in readable_day_names.items():
self.assertEqual(
days,
(actual["{}_score_count_taken".format(period)]
+ actual["{}_unknown_count".format(period)]
+ actual["{}_missed_count".format(period)])
)
self.assertAlmostEqual(
100,
(actual["{}_adherence_score".format(period)]
+ actual["{}_unknown_score".format(period)]
+ actual["{}_missed_score".format(period)]),
places=1
)
def test_adherence_score_by_source(self):
adherence_cases = [
{
"name": '1',
"adherence_source": "99DOTS",
"adherence_value": 'unobserved_dose',
"adherence_date": datetime.date(2015, 12, 31),
},
{
"name": '2',
"adherence_source": "99DOTS",
"adherence_value": 'unobserved_dose',
"adherence_date": datetime.date(2016, 1, 15),
},
{
"name": '5',
"adherence_source": "enikshay",
"adherence_report_source": "other",
"adherence_value": 'unobserved_dose',
"adherence_date": datetime.date(2016, 1, 17),
},
{
"name": '3',
"adherence_source": "99DOTS",
"adherence_value": 'unobserved_dose',
"adherence_date": datetime.date(2016, 1, 20),
},
{
"name": '4',
"adherence_source": "MERM",
"adherence_value": 'unobserved_dose',
"adherence_date": datetime.date(2016, 1, 30),
},
]
episode = self.create_episode_case(
adherence_schedule_date_start=datetime.date(2015, 12, 1),
adherence_schedule_id='schedule1',
adherence_cases=adherence_cases,
)
updater = EpisodeAdherenceUpdate(self.domain, episode)
updater.date_today_in_india = datetime.date(2016, 1, 31)
expected = {
'three_day_score_count_taken_99DOTS': 0,
'one_week_score_count_taken_99DOTS': 0,
'two_week_score_count_taken_99DOTS': 1,
'month_score_count_taken_99DOTS': 2,
'three_day_adherence_score_99DOTS': 0.0,
'one_week_adherence_score_99DOTS': 0.0,
'two_week_adherence_score_99DOTS': 7.14,
'month_adherence_score_99DOTS': 6.67,
'three_day_score_count_taken_MERM': 1,
'one_week_score_count_taken_MERM': 1,
'two_week_score_count_taken_MERM': 1,
'month_score_count_taken_MERM': 1,
'three_day_adherence_score_MERM': 33.33,
'one_week_adherence_score_MERM': 14.29,
'two_week_adherence_score_MERM': 7.14,
'month_adherence_score_MERM': 3.33,
'three_day_score_count_taken_other': 0,
'one_week_score_count_taken_other': 0,
'two_week_score_count_taken_other': 1,
'month_score_count_taken_other': 1,
'three_day_adherence_score_other': 0.0,
'one_week_adherence_score_other': 0.0,
'two_week_adherence_score_other': 7.14,
'month_adherence_score_other': 3.33,
'three_day_score_count_taken_treatment_supervisor': 0,
'one_week_score_count_taken_treatment_supervisor': 0,
'two_week_score_count_taken_treatment_supervisor': 0,
'month_score_count_taken_treatment_supervisor': 0,
'three_day_adherence_score_treatment_supervisor': 0.0,
'one_week_adherence_score_treatment_supervisor': 0.0,
'two_week_adherence_score_treatment_supervisor': 0.0,
'month_adherence_score_treatment_supervisor': 0.0,
}
self.assert_properties_equal(expected, updater.update_json())
def test_count_taken_by_day(self):
episode = self.create_episode_case(
adherence_schedule_date_start=datetime.date(2016, 1, 10),
adherence_schedule_id='schedule1',
adherence_cases=[]
)
episode_update = EpisodeAdherenceUpdate(self.domain, episode)
episode_update.purge_date = datetime.date(2016, 1, 20)
def dose_source_by_day(cases, day):
# cases a list of tuples
# (case_id, adherence_date, modified_on, adherence_value, source, closed, closure_reason)
return calculate_dose_status_by_day(
[
{
'adherence_source': source,
'adherence_date': str(dose_date), # the code expects string format
'adherence_value': dose_value,
'closed': closed,
'adherence_closure_reason': closure_reason,
'modified_on': modified_on,
}
for (_, dose_date, modified_on, dose_value, source, closed, closure_reason) in cases
]
)[day].source
## test enikshay only source, open cases
# not-taken - latest_modified_on case says no dose taken
self.assertEqual(
dose_source_by_day([
('some_id', datetime.date(2016, 1, 21), datetime.date(2016, 2, 21),
DTIndicators[0], 'enikshay', False, None),
('some_id', datetime.date(2016, 1, 21), datetime.date(2016, 2, 22),
DOSE_UNKNOWN, 'enikshay', False, None),
], datetime.date(2016, 1, 21)),
False
)
# taken - latest_modified_on case says dose taken
self.assertEqual(
dose_source_by_day([
('some_id', datetime.date(2016, 1, 22), datetime.date(2016, 2, 22),
DTIndicators[0], 'enikshay', False, None),
('some_id', datetime.date(2016, 1, 22), datetime.date(2016, 2, 21),
DOSE_UNKNOWN, 'enikshay', False, None),
], datetime.date(2016, 1, 22)),
'enikshay'
)
## test enikshay only source, closed/closure_reason cases
# not taken - as 1st case is not relevant because closed, closure_reason. 2nd case says no dose taken
self.assertEqual(
dose_source_by_day([
('some_id', datetime.date(2016, 1, 23), datetime.date(2016, 2, 22),
DTIndicators[0], 'enikshay', True, None),
('some_id', datetime.date(2016, 1, 23), datetime.date(2016, 2, 21),
DOSE_UNKNOWN, 'enikshay', False, None),
], datetime.date(2016, 1, 23)),
False
)
# taken - as 1st case is not relevant because closed, closure_reason. 2nd case says dose taken
self.assertEqual(
dose_source_by_day([
('some_id', datetime.date(2016, 1, 24), datetime.date(2016, 2, 22),
DOSE_UNKNOWN, 'enikshay', True, None),
('some_id', datetime.date(2016, 1, 24), datetime.date(2016, 2, 21),
DTIndicators[0], 'enikshay', False, None),
], datetime.date(2016, 1, 24)),
'enikshay'
)
# not taken - as 1st case is relevent case with latest_modified_on and says dose not taken
self.assertEqual(
dose_source_by_day([
('some_id', datetime.date(2016, 1, 25), datetime.date(2016, 2, 22),
DOSE_UNKNOWN, 'enikshay', True, HISTORICAL_CLOSURE_REASON),
('some_id', datetime.date(2016, 1, 25), datetime.date(2016, 2, 21),
DTIndicators[0], 'enikshay', False, None),
], datetime.date(2016, 1, 25)),
False
)
# taken - as 1st case is relevent case with latest_modified_on and says dose is taken
self.assertEqual(
dose_source_by_day([
('some_id', datetime.date(2016, 1, 26), datetime.date(2016, 2, 22),
DTIndicators[0], 'enikshay', True, HISTORICAL_CLOSURE_REASON),
('some_id', datetime.date(2016, 1, 26), datetime.date(2016, 2, 21),
DOSE_UNKNOWN, 'enikshay', False, None),
], datetime.date(2016, 1, 26)),
'enikshay'
)
## test non-enikshay source only cases
# not taken - non-enikshay source, so consider latest_modified_on
self.assertEqual(
dose_source_by_day([
('some_id', datetime.date(2016, 1, 27), datetime.date(2016, 2, 22),
DOSE_UNKNOWN, 'non-enikshay', True, 'a'),
('some_id', datetime.date(2016, 1, 27), datetime.date(2016, 2, 21),
DTIndicators[0], '99dots', False, None),
], datetime.date(2016, 1, 27)),
False
)
# taken - non-enikshay source, so consider latest_modified_on
self.assertEqual(
dose_source_by_day([
('some_id', datetime.date(2016, 1, 28), datetime.date(2016, 2, 22),
DTIndicators[0], '99DOTS', True, 'a'),
('some_id', datetime.date(2016, 1, 28), datetime.date(2016, 2, 21),
DOSE_UNKNOWN, '99DOTS', False, None),
], datetime.date(2016, 1, 28)),
'99DOTS'
)
## test mix of enikshay, non-enikshay sources
# taken - as enikshay source case says taken
self.assertEqual(
dose_source_by_day([
('some_id', datetime.date(2016, 1, 29), datetime.date(2016, 2, 22),
DTIndicators[0], '99', True, 'a'),
('some_id', datetime.date(2016, 1, 29), datetime.date(2016, 2, 21),
DTIndicators[0], 'enikshay', False, None),
], datetime.date(2016, 1, 29)),
'enikshay'
)
# not taken - as enikshay source case says not taken
self.assertEqual(
dose_source_by_day([
('some_id', datetime.date(2016, 1, 1), datetime.date(2016, 2, 22),
DTIndicators[0], '99', True, 'a'),
('some_id', datetime.date(2016, 1, 1), datetime.date(2016, 2, 21),
DOSE_UNKNOWN, 'enikshay', False, None),
], datetime.date(2016, 1, 1)),
False
)
# not taken - as the only enikshay source case is closed without valid-reason
self.assertEqual(
dose_source_by_day([
('some_id', datetime.date(2016, 1, 2), datetime.date(2016, 2, 22),
DTIndicators[0], '99', True, 'a'),
('some_id', datetime.date(2016, 1, 2), datetime.date(2016, 2, 21),
DTIndicators[0], 'enikshay', True, None),
], datetime.date(2016, 1, 2)),
False
)
# taken - as the only enikshay source case is closed with right closure_reason
self.assertEqual(
dose_source_by_day([
('some_id', datetime.date(2016, 1, 3), datetime.date(2016, 2, 22),
DOSE_UNKNOWN, '99', True, 'a'),
('some_id', datetime.date(2016, 1, 3), datetime.date(2016, 2, 21),
DTIndicators[0], 'enikshay', True, HISTORICAL_CLOSURE_REASON),
], datetime.date(2016, 1, 3)),
'enikshay'
)
def test_count_doses_taken_by_source(self):
adherence_cases = [
{
"name": 'Bad source shouldnt show up',
"adherence_source": "enikshay",
"adherence_report_source": "Bad source",
"adherence_value": 'unobserved_dose',
"adherence_date": datetime.date(2017, 8, 14),
},
{
"name": '1',
"adherence_source": "99DOTS",
"adherence_value": 'unobserved_dose',
"adherence_date": datetime.date(2017, 8, 15),
},
{
"name": '2',
"adherence_source": "99DOTS",
"adherence_value": 'unobserved_dose',
"adherence_date": datetime.date(2017, 8, 16),
},
{
"name": '3',
"adherence_source": "99DOTS",
"adherence_value": 'unobserved_dose',
"adherence_date": datetime.date(2017, 8, 17),
},
{
"name": '4',
"adherence_source": "MERM",
"adherence_value": 'unobserved_dose',
"adherence_date": datetime.date(2017, 8, 18),
},
{
"name": 'overwrites 99DOTS case',
"adherence_source": "enikshay",
"adherence_value": 'unobserved_dose',
"adherence_report_source": "treatment_supervisor",
"adherence_date": datetime.date(2017, 8, 16), # overwrites the 99DOTS case of this date
}
]
episode = self.create_episode_case(
adherence_schedule_date_start=datetime.date(2017, 8, 12),
adherence_schedule_id='schedule1',
adherence_cases=adherence_cases,
)
updater = EpisodeAdherenceUpdate(self.domain, episode)
updater.purge_date = datetime.date(2017, 8, 10),
dose_status_by_day = calculate_dose_status_by_day(updater.get_valid_adherence_cases())
self.assertDictEqual(
{
'99DOTS': 2,
'MERM': 1,
'treatment_supervisor': 1,
},
EpisodeAdherenceUpdate.count_doses_taken_by_source(dose_status_by_day)
)
self.assertDictEqual(
{
'99DOTS': 1,
'MERM': 1,
},
EpisodeAdherenceUpdate.count_doses_taken_by_source(
dose_status_by_day,
start_date=datetime.date(2017, 8, 17),
end_date=datetime.date(2017, 8, 18)
)
)