def testPillboxCheck(self):
"""
This test tries to accomplish a few things
0: ensure the content of the signal is correctly set
1: verify that the dots_observations view is working correctly in reporting dates correclty back in order
2: Ensure that if you fill out the questions on the form, it won't redundantly fill out the pillbox cells again as well
3: ensure that proper ART/NonART sequences are put in the correct buckets when combined into a "DOTS Day" cell
todo: get label day_slot to work correctly
"""
#check to make sure that 0th and nth elements are where they ought to be
#hit the VIEW to make sure it's there
#make sure the pact_dots_data signal is working
#check no pillbox check entries that entries show up, and NOTHING more.
#ensure signal works
#todo: labeling checks
self.testSignal()
observations = query_observations(CASE_ID, START_DATE, END_DATE)
td = END_DATE - START_DATE
def check_obs_props(obs, props):
for k, v in props.items():
if k.endswith("_date"):
#datetime check
obs_date = getattr(obs, k).date()
val_date = dateutil.parser.parse(v).date()
self.assertEquals(obs_date, val_date)
else:
self.assertEquals(
getattr(obs, k),
v,
msg="Error, observation %s\n\t%s didn't match: %s != %s"
% (simplejson.dumps(obs.to_json(),
indent=4), k, getattr(obs, k), v))
for d in range(td.days):
this_day = START_DATE + timedelta(days=d)
day_submissions = filter_obs_for_day(this_day.date(), observations)
day_data = DOTDay.merge_from_observations(day_submissions)
if this_day.date() == START_DATE.date():
art_first = day_data.art.dose_dict[1][0]
art_first_check_props = {
"encounter_date": "2012-12-07T05:00:00Z",
"total_doses": 2,
"day_note": "art first noon",
"day_index": 20,
"note": "",
"pact_id": "999999",
"provider": "ctsims",
"method": "pillbox",
"observed_date": "2012-11-17T05:00:00Z",
#"day_slot": 1,
"completed_date": "2012-12-16T22:00:28Z",
"adherence": "partial",
"dose_number": 1, #zero indexed
# "doc_type": "CObservation",
"is_reconciliation": False,
"anchor_date": "2012-12-07T05:00:00Z",
"created_date": "2012-12-16T21:37:52Z",
"is_art": True,
"_id": "a1811d7e-c968-4b63-aea5-6195ce0d8759",
"doc_id": "a1811d7e-c968-4b63-aea5-6195ce0d8759"
}
check_obs_props(art_first, art_first_check_props)
non_art_first_1 = day_data.nonart.dose_dict[1][0]
non_art_first_1_props = {
"encounter_date": "2012-12-07T05:00:00Z",
"total_doses": 3,
"day_note": "non art first evening",
"day_index": 20,
"note": "",
"pact_id": "999999",
"provider": "ctsims",
"method": "pillbox",
"observed_date": "2012-11-17T05:00:00Z",
# "day_slot": 2,
"completed_date": "2012-12-16T22:00:28Z",
"adherence": "partial",
"dose_number": 1,
# "doc_type": "CObservation",
"is_reconciliation": False,
"anchor_date": "2012-12-07T05:00:00Z",
"created_date": "2012-12-16T21:37:52Z",
"is_art": False,
"_id": "a1811d7e-c968-4b63-aea5-6195ce0d8759",
"doc_id": "a1811d7e-c968-4b63-aea5-6195ce0d8759"
}
check_obs_props(non_art_first_1, non_art_first_1_props)
non_art_first_2 = day_data.nonart.dose_dict[2][0]
non_art_first_2_props = {
"encounter_date": "2012-12-07T05:00:00Z",
"total_doses": 3,
"day_note": "non art bedtime first",
"day_index": 20,
"note": "",
"pact_id": "999999",
"provider": "ctsims",
"method": "pillbox",
"observed_date": "2012-11-17T05:00:00Z",
# "day_slot": 3,
"completed_date": "2012-12-16T22:00:28Z",
"adherence": "partial",
"dose_number": 2,
# "doc_type": "CObservation",
"is_reconciliation": False,
"anchor_date": "2012-12-07T05:00:00Z",
"created_date": "2012-12-16T21:37:52Z",
"is_art": False,
"_id": "a1811d7e-c968-4b63-aea5-6195ce0d8759",
"doc_id": "a1811d7e-c968-4b63-aea5-6195ce0d8759"
}
check_obs_props(non_art_first_2, non_art_first_2_props)
if this_day.date() == (ANCHOR_DATE - timedelta(days=1)).date():
self.assertEquals(
len(day_data.art.dose_dict.keys()), 2
) # two doses, one for the answered, another for unchecked
art_slast = day_data.art.dose_dict[0][0]
art_slast_props = {
"encounter_date": "2012-12-07T05:00:00Z",
"total_doses": 2,
"day_note": "2nd to last last filled by questions",
"day_index": 1,
"note": "",
"pact_id": "999999",
"provider": "ctsims",
"method": "pillbox",
"observed_date": "2012-12-06T05:00:00Z",
"day_slot": -1,
"completed_date": "2012-12-16T22:00:28Z",
"adherence": "partial",
"dose_number": 0,
# "doc_type": "CObservation",
"is_reconciliation": False,
"anchor_date": "2012-12-07T05:00:00Z",
"created_date": "2012-12-16T21:37:52Z",
"is_art": True,
"_id": "a1811d7e-c968-4b63-aea5-6195ce0d8759",
"doc_id": "a1811d7e-c968-4b63-aea5-6195ce0d8759"
}
check_obs_props(art_slast, art_slast_props)
nonart_slast0 = day_data.nonart.dose_dict[0][0]
non_art0 = {
"encounter_date": "2012-12-07T05:00:00Z",
"total_doses": 3,
"day_note": "",
"day_index": 1,
"note": "",
"pact_id": "999999",
"provider": "ctsims",
"method": "direct",
"observed_date": "2012-12-06T05:00:00Z",
# "day_slot": -1,
"completed_date": "2012-12-16T22:00:28Z",
"adherence": "empty",
"dose_number": 0,
# "doc_type": "CObservation",
"is_reconciliation": False,
"anchor_date": "2012-12-07T05:00:00Z",
"created_date": "2012-12-16T21:37:52Z",
"is_art": False,
"_id": "a1811d7e-c968-4b63-aea5-6195ce0d8759",
"doc_id": "a1811d7e-c968-4b63-aea5-6195ce0d8759"
}
check_obs_props(nonart_slast0, non_art0)
nonart_slast1 = day_data.nonart.dose_dict[1][0]
non_art1 = {
"encounter_date": "2012-12-07T05:00:00Z",
"total_doses": 3,
"day_note": "non art noon second to last",
"day_index": 1,
"note": "",
"pact_id": "999999",
"provider": "ctsims",
"method": "pillbox",
"observed_date": "2012-12-06T05:00:00Z",
# "day_slot": -1,
"completed_date": "2012-12-16T22:00:28Z",
"adherence": "partial",
"dose_number": 1,
# "doc_type": "CObservation",
"is_reconciliation": False,
"anchor_date": "2012-12-07T05:00:00Z",
"created_date": "2012-12-16T21:37:52Z",
"is_art": False,
"_id": "a1811d7e-c968-4b63-aea5-6195ce0d8759",
"doc_id": "a1811d7e-c968-4b63-aea5-6195ce0d8759"
}
check_obs_props(nonart_slast1, non_art1)
nonart_slast2 = day_data.nonart.dose_dict[2][0]
non_art2 = {
"encounter_date": "2012-12-07T05:00:00Z",
"total_doses": 3,
"day_note": "art evening second to last",
"day_index": 1,
"note": "",
"pact_id": "999999",
"provider": "ctsims",
"method": "pillbox",
"observed_date": "2012-12-06T05:00:00Z",
# "day_slot": -1,
"completed_date": "2012-12-16T22:00:28Z",
"adherence": "partial",
"dose_number": 2,
# "doc_type": "CObservation",
"is_reconciliation": False,
"anchor_date": "2012-12-07T05:00:00Z",
"created_date": "2012-12-16T21:37:52Z",
"is_art": False,
"_id": "a1811d7e-c968-4b63-aea5-6195ce0d8759",
"doc_id": "a1811d7e-c968-4b63-aea5-6195ce0d8759"
}
check_obs_props(nonart_slast2, non_art2)
if this_day.date() == ANCHOR_DATE.date():
self.assertEqual(len(day_data.nonart.dose_dict[0]), 1)
non_art_last = day_data.nonart.dose_dict[0][0]
non_art_last_props = {
"encounter_date": "2012-12-07T05:00:00Z",
"total_doses": 3,
"day_note": "",
"day_index": 0,
"note": "Anchor same",
"pact_id": "999999",
"provider": "ctsims",
"method": "direct",
"observed_date": "2012-12-07T05:00:00Z",
#"day_slot": -1,
"completed_date": "2012-12-16T22:00:28Z",
"adherence": "partial",
"dose_number": 0,
# "doc_type": "CObservation",
"is_reconciliation": False,
"anchor_date": "2012-12-07T05:00:00Z",
"created_date": "2012-12-16T21:37:52Z",
"is_art": False,
"_id": "a1811d7e-c968-4b63-aea5-6195ce0d8759",
"doc_id": "a1811d7e-c968-4b63-aea5-6195ce0d8759"
}
check_obs_props(non_art_last, non_art_last_props)
non_art_last_noon = day_data.nonart.dose_dict[1][0]
non_art_last_noon_props = {
"encounter_date": "2012-12-07T05:00:00Z",
"total_doses": 3,
"day_note": "non art noon last",
"day_index": 0,
"note": "Anchor same",
"pact_id": "999999",
"provider": "ctsims",
"method": "pillbox",
"observed_date": "2012-12-07T05:00:00Z",
# "day_slot": -1,
"completed_date": "2012-12-16T22:00:28Z",
"adherence": "partial",
"dose_number": 1,
# "doc_type": "CObservation",
"is_reconciliation": False,
"anchor_date": "2012-12-07T05:00:00Z",
"created_date": "2012-12-16T21:37:52Z",
"is_art": False,
"_id": "a1811d7e-c968-4b63-aea5-6195ce0d8759",
"doc_id": "a1811d7e-c968-4b63-aea5-6195ce0d8759"
}
check_obs_props(non_art_last_noon, non_art_last_noon_props)
#todo: check reconciliation?
pass
def testPillboxCheck(self):
"""
This test tries to accomplish a few things
0: ensure the content of the signal is correctly set
1: verify that the dots_observations view is working correctly in reporting dates correclty back in order
2: Ensure that if you fill out the questions on the form, it won't redundantly fill out the pillbox cells again as well
3: ensure that proper ART/NonART sequences are put in the correct buckets when combined into a "DOTS Day" cell
todo: get label day_slot to work correctly
"""
#check to make sure that 0th and nth elements are where they ought to be
#hit the VIEW to make sure it's there
#make sure the pact_dots_data signal is working
#check no pillbox check entries that entries show up, and NOTHING more.
#ensure signal works
#todo: labeling checks
self.testSignal()
observations = query_observations(CASE_ID, START_DATE, END_DATE)
td = END_DATE - START_DATE
def check_obs_props(obs, props):
for k, v in props.items():
if k.endswith("_date"):
# datetime check
obs_datetime = getattr(obs, k)
val_datetime = dateutil.parser.parse(v)
if k in ('completed_date', 'created_date'):
obs_datetime = ServerTime(obs_datetime).user_time(PACT_TIMEZONE).done()
obs_date = obs_datetime.date()
val_date = val_datetime.date()
self.assertEquals(obs_date, val_date)
else:
self.assertEquals(getattr(obs, k), v,
msg="Error, observation %s\n\t%s didn't match: %s != %s" % (
json.dumps(obs.to_json(), indent=4), k, getattr(obs, k),
v))
for d in range(td.days):
this_day = START_DATE + timedelta(days=d)
day_submissions = filter_obs_for_day(this_day.date(), observations)
day_data = DOTDay.merge_from_observations(day_submissions)
if this_day.date() == START_DATE.date():
art_first = day_data.art.dose_dict[1][0]
art_first_check_props = {
"encounter_date": "2012-12-07T05:00:00Z",
"total_doses": 2,
"day_note": "art first noon",
"day_index": 20,
"note": "",
"pact_id": "999999",
"provider": "ctsims",
"method": "pillbox",
"observed_date": "2012-11-17T05:00:00Z",
#"day_slot": 1,
"completed_date": "2012-12-16T22:00:28.847000Z",
"adherence": "partial",
"dose_number": 1, #zero indexed
# "doc_type": "CObservation",
"is_reconciliation": False,
"anchor_date": "2012-12-07T05:00:00Z",
"created_date": "2012-12-16T21:37:52.771000Z",
"is_art": True,
"_id": "a1811d7e-c968-4b63-aea5-6195ce0d8759",
"doc_id": "a1811d7e-c968-4b63-aea5-6195ce0d8759"
}
check_obs_props(art_first, art_first_check_props)
non_art_first_1 = day_data.nonart.dose_dict[1][0]
non_art_first_1_props = {
"encounter_date": "2012-12-07T05:00:00Z",
"total_doses": 3,
"day_note": "non art first evening",
"day_index": 20,
"note": "",
"pact_id": "999999",
"provider": "ctsims",
"method": "pillbox",
"observed_date": "2012-11-17T05:00:00Z",
# "day_slot": 2,
"completed_date": "2012-12-16T22:00:28.847000Z",
"adherence": "partial",
"dose_number": 1,
# "doc_type": "CObservation",
"is_reconciliation": False,
"anchor_date": "2012-12-07T05:00:00Z",
"created_date": "2012-12-16T21:37:52.771000Z",
"is_art": False,
"_id": "a1811d7e-c968-4b63-aea5-6195ce0d8759",
"doc_id": "a1811d7e-c968-4b63-aea5-6195ce0d8759"
}
check_obs_props(non_art_first_1, non_art_first_1_props)
non_art_first_2 = day_data.nonart.dose_dict[2][0]
non_art_first_2_props = {
"encounter_date": "2012-12-07T05:00:00Z",
"total_doses": 3,
"day_note": "non art bedtime first",
"day_index": 20,
"note": "",
"pact_id": "999999",
"provider": "ctsims",
"method": "pillbox",
"observed_date": "2012-11-17T05:00:00Z",
# "day_slot": 3,
"completed_date": "2012-12-16T22:00:28.847000Z",
"adherence": "partial",
"dose_number": 2,
# "doc_type": "CObservation",
"is_reconciliation": False,
"anchor_date": "2012-12-07T05:00:00Z",
"created_date": "2012-12-16T21:37:52.771000Z",
"is_art": False,
"_id": "a1811d7e-c968-4b63-aea5-6195ce0d8759",
"doc_id": "a1811d7e-c968-4b63-aea5-6195ce0d8759"
}
check_obs_props(non_art_first_2, non_art_first_2_props)
if this_day.date() == (ANCHOR_DATE - timedelta(days=1)).date():
self.assertEquals(len(day_data.art.dose_dict.keys()),
2) # two doses, one for the answered, another for unchecked
art_slast = day_data.art.dose_dict[0][0]
art_slast_props = {
"encounter_date": "2012-12-07T05:00:00Z",
"total_doses": 2,
"day_note": "2nd to last last filled by questions",
"day_index": 1,
"note": "",
"pact_id": "999999",
"provider": "ctsims",
"method": "pillbox",
"observed_date": "2012-12-06T05:00:00Z",
"day_slot": -1,
"completed_date": "2012-12-16T22:00:28.847000Z",
"adherence": "partial",
"dose_number": 0,
# "doc_type": "CObservation",
"is_reconciliation": False,
"anchor_date": "2012-12-07T05:00:00Z",
"created_date": "2012-12-16T21:37:52.771000Z",
"is_art": True,
"_id": "a1811d7e-c968-4b63-aea5-6195ce0d8759",
"doc_id": "a1811d7e-c968-4b63-aea5-6195ce0d8759"
}
check_obs_props(art_slast, art_slast_props)
nonart_slast0 = day_data.nonart.dose_dict[0][0]
non_art0 = {
"encounter_date": "2012-12-07T05:00:00Z",
"total_doses": 3,
"day_note": "",
"day_index": 1,
"note": "",
"pact_id": "999999",
"provider": "ctsims",
"method": "direct",
"observed_date": "2012-12-06T05:00:00Z",
# "day_slot": -1,
"completed_date": "2012-12-16T22:00:28.847000Z",
"adherence": "empty",
"dose_number": 0,
# "doc_type": "CObservation",
"is_reconciliation": False,
"anchor_date": "2012-12-07T05:00:00Z",
"created_date": "2012-12-16T21:37:52.771000Z",
"is_art": False,
"_id": "a1811d7e-c968-4b63-aea5-6195ce0d8759",
"doc_id": "a1811d7e-c968-4b63-aea5-6195ce0d8759"
}
check_obs_props(nonart_slast0, non_art0)
nonart_slast1 = day_data.nonart.dose_dict[1][0]
non_art1 = {
"encounter_date": "2012-12-07T05:00:00Z",
"total_doses": 3,
"day_note": "non art noon second to last",
"day_index": 1,
"note": "",
"pact_id": "999999",
"provider": "ctsims",
"method": "pillbox",
"observed_date": "2012-12-06T05:00:00Z",
# "day_slot": -1,
"completed_date": "2012-12-16T22:00:28.847000Z",
"adherence": "partial",
"dose_number": 1,
# "doc_type": "CObservation",
"is_reconciliation": False,
"anchor_date": "2012-12-07T05:00:00Z",
"created_date": "2012-12-16T21:37:52.771000Z",
"is_art": False,
"_id": "a1811d7e-c968-4b63-aea5-6195ce0d8759",
"doc_id": "a1811d7e-c968-4b63-aea5-6195ce0d8759"
}
check_obs_props(nonart_slast1, non_art1)
nonart_slast2 = day_data.nonart.dose_dict[2][0]
non_art2 = {
"encounter_date": "2012-12-07T05:00:00Z",
"total_doses": 3,
"day_note": "art evening second to last",
"day_index": 1,
"note": "",
"pact_id": "999999",
"provider": "ctsims",
"method": "pillbox",
"observed_date": "2012-12-06T05:00:00Z",
# "day_slot": -1,
"completed_date": "2012-12-16T22:00:28.847000Z",
"adherence": "partial",
"dose_number": 2,
# "doc_type": "CObservation",
"is_reconciliation": False,
"anchor_date": "2012-12-07T05:00:00Z",
"created_date": "2012-12-16T21:37:52.771000Z",
"is_art": False,
"_id": "a1811d7e-c968-4b63-aea5-6195ce0d8759",
"doc_id": "a1811d7e-c968-4b63-aea5-6195ce0d8759"
}
check_obs_props(nonart_slast2, non_art2)
if this_day.date() == ANCHOR_DATE.date():
self.assertEqual(len(day_data.nonart.dose_dict[0]), 1)
non_art_last = day_data.nonart.dose_dict[0][0]
non_art_last_props = {
"encounter_date": "2012-12-07T05:00:00Z",
"total_doses": 3,
"day_note": "",
"day_index": 0,
"note": "Anchor same",
"pact_id": "999999",
"provider": "ctsims",
"method": "direct",
"observed_date": "2012-12-07T05:00:00Z",
#"day_slot": -1,
"completed_date": "2012-12-16T22:00:28.847000Z",
"adherence": "partial",
"dose_number": 0,
# "doc_type": "CObservation",
"is_reconciliation": False,
"anchor_date": "2012-12-07T05:00:00Z",
"created_date": "2012-12-16T21:37:52.771000Z",
"is_art": False,
"_id": "a1811d7e-c968-4b63-aea5-6195ce0d8759",
"doc_id": "a1811d7e-c968-4b63-aea5-6195ce0d8759"
}
check_obs_props(non_art_last, non_art_last_props)
non_art_last_noon = day_data.nonart.dose_dict[1][0]
non_art_last_noon_props = {
"encounter_date": "2012-12-07T05:00:00Z",
"total_doses": 3,
"day_note": "non art noon last",
"day_index": 0,
"note": "Anchor same",
"pact_id": "999999",
"provider": "ctsims",
"method": "pillbox",
"observed_date": "2012-12-07T05:00:00Z",
# "day_slot": -1,
"completed_date": "2012-12-16T22:00:28.847000Z",
"adherence": "partial",
"dose_number": 1,
# "doc_type": "CObservation",
"is_reconciliation": False,
"anchor_date": "2012-12-07T05:00:00Z",
"created_date": "2012-12-16T21:37:52.771000Z",
"is_art": False,
"_id": "a1811d7e-c968-4b63-aea5-6195ce0d8759",
"doc_id": "a1811d7e-c968-4b63-aea5-6195ce0d8759"
}
check_obs_props(non_art_last_noon, non_art_last_noon_props)
#todo: check reconciliation?
pass
def formatday(self, day, weekday):
if day != 0:
cssclass = self.cssclasses[weekday]
this_day = date(self.year, self.month, day)
if date.today() == this_day:
cssclass += ' today'
if date.today() < this_day:
future=True
else:
future=False
day_observations = filter_obs_for_day(this_day, self.observations)
if len(day_observations) > 0:
cssclass += ' filled'
body = ['<div class="calendar-cell">']
day_data = DOTDay.merge_from_observations(day_observations)
#day_data = merge_dot_day(day_observations)
#for drug_type in day_data.keys():
day_notes = set()
for dose_data in [day_data.nonart, day_data.art]:
body.append('')
body.append('<div class="drug-cell">')
body.append('<div class="drug-label">%s</div>' % dose_data.drug_class)
#drug_total = day_data[drug_type]['total_doses']
drug_total = dose_data.total_doses
for dose_num, obs_list in dose_data.dose_dict.items():
if len(obs_list) > 0:
obs = obs_list[0]
if obs.day_note is not None and len(obs.day_note) > 0:
day_notes.add(obs.day_note)
if obs.day_slot != '' and obs.day_slot is not None and obs.day_slot != -1:
day_slot_string = DAY_SLOTS_BY_IDX.get(int(obs.day_slot), 'Unknown').title()
body.append('<div class="time-label">%s</div>' % day_slot_string)
else:
#do it by seq?
body.append('<div class="time-label">Dose %d</div>' % (int(dose_num) + 1))
body.append('<div class="time-cell">')
body.append('<div class="observation">')
if obs.adherence == DOT_ADHERENCE_UNCHECKED:
body.append('<span style="font-size:85%;color:#888;font-style:italic;">unchecked</span>')
else:
if obs.adherence == DOT_ADHERENCE_EMPTY:
# body.append('<span class="label label-success">Empty</span>')
body.append('<img src="%spact/icons/check.jpg">' % settings.STATIC_URL)
elif obs.adherence == DOT_ADHERENCE_PARTIAL:
# body.append('<span class="label label-warning">Partial</span>')
body.append('<img src="%spact/icons/exclamation-point.jpg">' % settings.STATIC_URL)
elif obs.adherence == DOT_ADHERENCE_FULL:
# body.append('<span class="label label-important">Full</span>')
body.append('<img src="%spact/icons/x-mark.png">' % settings.STATIC_URL)
if obs.method == DOT_OBSERVATION_DIRECT:
# body.append('<span class="label label-info">Direct</span>')
body.append('<img src="%spact/icons/plus.png">' % settings.STATIC_URL)
elif obs.method == DOT_OBSERVATION_PILLBOX:
# body.append('<span class="label label-inverse">Pillbox</span>')
body.append('<img src="%spact/icons/bucket.png">' % settings.STATIC_URL)
elif obs.method == DOT_OBSERVATION_SELF:
# body.append('<span class="label">Self</span>')
body.append('<img src="%spact/icons/minus.png">' % settings.STATIC_URL)
body.append(' </div> <!-- close time-cell -->') #close time-cell
# body.append(' </div>') #close observation
else:
#empty observations for this dose_num
body.append('<div class="time-label">Dose %d</div>' % (int(dose_num) + 1))
body.append('<div class="time-cell">')
body.append('<div class="observation">')
body.append("empty! </div>")
# body.append(' </div>')
body.append(' </div> <!-- close observation -->') #close observation
body.append(' </div> <!-- close calendar cell -->') # close calendar-cell
if len(day_notes) > 0 :
body.append('<div class="date-notes-block">')
body.append('<i class="icon-info-sign"></i> ')
body.append('<small>%s</small>' % ('<br>'.join(day_notes)))
body.append('</div> <!-- end notes -->')
return self.day_cell(cssclass, '%d %s' % (day, ''.join(body)))
if weekday < 5 and not future:
missing_link = []
return self.day_cell(cssclass, "%d %s" % (day, ''.join(missing_link)))
elif weekday < 5 and future:
return self.day_cell('future', "%d" % day)
else:
return self.day_cell(cssclass, day)
return self.day_cell('noday', ' ')