def fhd_submission_stats(request, district_id=None):
stats = [] # columns to be sent to generic start out as blank
user_location = Location.objects.get(pk=district_id) if district_id else get_location_for_user(request.user)
location = Location.tree.root_nodes()[0]
dates = get_xform_dates(request)
values = total_attribute_value(['dpt_males'], start_date=dates.get('start'), end_date=dates.get('end'), location=location)
stats.append(('males', location_values(user_location, values)))
values = total_attribute_value(['dpt_females'], start_date=dates.get('start'), end_date=dates.get('end'), location=location)
stats.append(('females', location_values(user_locaiton, values)))
res = {'dates': dates, 'stats': stats}
return res
def notifiable_disease_test(request):
METRICS = {
'malaria': {
'threshold': 3,
'slug': 'cases_ma',
'gen': mk_notifiable_disease_alert,
}
}
REPORTING_INTERVAL = 'weekly'
timestamp = datetime.now()
if REPORTING_INTERVAL == 'weekly':
yr, wk, dow = timestamp.isocalendar()
reporting_period = '%dw%02d' % (yr, wk)
#period_start = timestamp.date() - timedelta(days=dow - 1)
#period_end = period_start + timedelta(days=6)
period_start = datetime(2012, 1, 1)
period_end = timestamp
print period_start, period_end
else:
raise Exception('unsupported reporting interval [%s]' % REPORTING_INTERVAL)
for metric, info in METRICS.iteritems():
#todo: is the end date inclusive or exclusive?
data = total_attribute_value(info['slug'], period_start, period_end, Location.objects.get(name='Uganda'))
for total in data:
loc = Location.objects.get(id=total['location_id'])
val = total['value']
if val > info['threshold']:
# trigger alert
yield info['gen'](metric, 'alerts._prototyping.NotifiableDiseaseThresholdAlert', reporting_period, val, loc)
def abuse_stats(request, district_id=None):
stats = []
user_location = get_location(request, district_id)
location = Location.tree.root_nodes()[0]
start_date, end_date = previous_calendar_month()
dates = {"start": start_date, "end": end_date}
values = total_attribute_value("gemabuse_cases", start_date=start_date, end_date=end_date, location=location)
stats.append(("GEM reported abuse cases", location_values(user_location, values)))
htabuse = (
Poll.objects.get(name="emis_abuse")
.responses.exclude(has_errors=True)
.filter(date__range=(start_date, end_date))
.filter(
message__connection__contact__emisreporter__reporting_location__in=user_location.get_descendants(
include_self=True
).all()
)
.values("eav_values__value_int")
.annotate(Sum("eav_values__value_int"))
.values_list("eav_values__value_int__sum", flat=True)
)
stats.append(("headteacher reported abuse cases", htabuse[0] if htabuse[0] else "-"))
res = {}
res["dates"] = dates
res["stats"] = stats
return res
def attendance_stats(district):
stats = []
location = Location.tree.root_nodes()[0]
start_date, end_date = previous_calendar_week()
dates = {'start':start_date, 'end':end_date}
# import pdb;pdb.set_trace()
boys = ["boys_%s" % g for g in GRADES]
values = total_attribute_value(boys, start_date=start_date, end_date=end_date, location=location)
stats.append(('boys', location_values(district, values)))
girls = ["girls_%s" % g for g in GRADES]
values = total_attribute_value(girls, start_date=start_date, end_date=end_date, location=location)
stats.append(('girls', location_values(district, values)))
total_pupils = ["boys_%s" % g for g in GRADES] + ["girls_%s" % g for g in GRADES]
values = total_attribute_value(total_pupils, start_date=start_date, end_date=end_date, location=location)
stats.append(('total pupils', location_values(district, values)))
values = total_attribute_value("teachers_f", start_date=start_date, end_date=end_date, location=location)
stats.append(('female teachers', location_values(district, values)))
values = total_attribute_value("teachers_m", start_date=start_date, end_date=end_date, location=location)
stats.append(('male teachers', location_values(district, values)))
values = total_attribute_value(["teachers_f", "teachers_m"], start_date=start_date, end_date=end_date, location=location)
stats.append(('total teachers', location_values(district, values)))
res = {}
res['dates'] = dates
res['stats'] = stats
return res
def attendance_stats(district):
stats = []
location = Location.tree.root_nodes()[0]
start_date, end_date = previous_calendar_week()
dates = {'start': start_date, 'end': end_date}
# import pdb;pdb.set_trace()
boys = ["boys_%s" % g for g in GRADES]
values = total_attribute_value(boys,
start_date=start_date,
end_date=end_date,
location=location)
stats.append(('boys', location_values(district, values)))
girls = ["girls_%s" % g for g in GRADES]
values = total_attribute_value(girls,
start_date=start_date,
end_date=end_date,
location=location)
stats.append(('girls', location_values(district, values)))
total_pupils = ["boys_%s" % g
for g in GRADES] + ["girls_%s" % g for g in GRADES]
values = total_attribute_value(total_pupils,
start_date=start_date,
end_date=end_date,
location=location)
stats.append(('total pupils', location_values(district, values)))
values = total_attribute_value("teachers_f",
start_date=start_date,
end_date=end_date,
location=location)
stats.append(('female teachers', location_values(district, values)))
values = total_attribute_value("teachers_m",
start_date=start_date,
end_date=end_date,
location=location)
stats.append(('male teachers', location_values(district, values)))
values = total_attribute_value(["teachers_f", "teachers_m"],
start_date=start_date,
end_date=end_date,
location=location)
stats.append(('total teachers', location_values(district, values)))
res = {}
res['dates'] = dates
res['stats'] = stats
return res
def enrollment_stats(request, district_id=None):
stats = []
user_location = get_location(request, district_id)
location = Location.tree.root_nodes()[0]
# start_date, end_date = previous_calendar_week()
start_date = datetime.datetime(datetime.datetime.now().year, 1, 1)
end_date = datetime.datetime.now()
dates = {"start": start_date, "end": end_date}
boys = ["enrolledb_%s" % g for g in GRADES]
values = total_attribute_value(boys, start_date=start_date, end_date=end_date, location=location)
stats.append(("boys", location_values(user_location, values)))
girls = ["enrolledg_%s" % g for g in GRADES]
values = total_attribute_value(girls, start_date=start_date, end_date=end_date, location=location)
stats.append(("girls", location_values(user_location, values)))
total_pupils = ["enrolledb_%s" % g for g in GRADES] + ["enrolledg_%s" % g for g in GRADES]
values = total_attribute_value(total_pupils, start_date=start_date, end_date=end_date, location=location)
stats.append(("total pupils", location_values(user_location, values)))
values = total_attribute_value("deploy_f", start_date=start_date, end_date=end_date, location=location)
stats.append(("female teachers", location_values(user_location, values)))
values = total_attribute_value("deploy_m", start_date=start_date, end_date=end_date, location=location)
stats.append(("male teachers", location_values(user_location, values)))
values = total_attribute_value(
["deploy_f", "deploy_m"], start_date=start_date, end_date=end_date, location=location
)
stats.append(("total teachers", location_values(user_location, values)))
headteachers = School.objects.filter(location__in=user_location.get_descendants(include_self=True)).count()
stats.append(("total head teachers", headteachers))
stats.append(("total schools", headteachers))
res = {}
res["dates"] = dates
res["stats"] = stats
return res
def add_to_report(self, report, key, dictionary):
val = total_attribute_value(self.keyword, self.start_date, self.end_date, report.location, self.extra_filters)
reorganize_location(key, val, dictionary)
def attendance_stats(request, district_id=None):
stats = []
user_location = get_location(request, district_id)
location = Location.tree.root_nodes()[0]
start_date, end_date = previous_calendar_week()
dates = {"start": start_date, "end": end_date}
# import pdb;pdb.set_trace()
boys = ["boys_%s" % g for g in GRADES]
values = total_attribute_value(boys, start_date=start_date, end_date=end_date, location=location)
stats.append(("boys", location_values(user_location, values)))
girls = ["girls_%s" % g for g in GRADES]
values = total_attribute_value(girls, start_date=start_date, end_date=end_date, location=location)
stats.append(("girls", location_values(user_location, values)))
total_pupils = ["boys_%s" % g for g in GRADES] + ["girls_%s" % g for g in GRADES]
values = total_attribute_value(total_pupils, start_date=start_date, end_date=end_date, location=location)
attendance_ratio = location_values(user_location, values)
stats.append(("total pupils", location_values(user_location, values)))
enrolled_total = ["enrolledb_%s" % g for g in GRADES] + ["enrolledg_%s" % g for g in GRADES]
values = total_attribute_value(
enrolled_total,
start_date=datetime.datetime(datetime.datetime.now().year, 1, 1),
end_date=datetime.datetime.now(),
location=location,
)
if (
not type(location_values(user_location, values)) == str
and not type(attendance_ratio) == str
and location_values(user_location, values) > 0
):
attendance_ratio /= float(location_values(user_location, values))
if type(attendance_ratio) == str:
stats.append(("% absent", "-"))
else:
stats.append(("% absent", "%0.1f%%" % (100 - (attendance_ratio * 100))))
values = total_attribute_value("teachers_f", start_date=start_date, end_date=end_date, location=location)
stats.append(("female teachers", location_values(user_location, values)))
values = total_attribute_value("teachers_m", start_date=start_date, end_date=end_date, location=location)
stats.append(("male teachers", location_values(user_location, values)))
values = total_attribute_value(
["teachers_f", "teachers_m"], start_date=start_date, end_date=end_date, location=location
)
attendance_ratio = location_values(user_location, values)
stats.append(("total teachers", location_values(user_location, values)))
enrolled_total = ["deploy_f", "deploy_m"]
values = total_attribute_value(
enrolled_total,
start_date=datetime.datetime(datetime.datetime.now().year, 1, 1),
end_date=datetime.datetime.now(),
location=location,
)
if (
not type(location_values(user_location, values)) == str
and not type(attendance_ratio) == str
and location_values(user_location, values) > 0
):
attendance_ratio /= float(location_values(user_location, values))
if type(attendance_ratio) == str:
stats.append(("% absent", "-"))
else:
stats.append(("% absent", "%0.1f%%" % (100 - (attendance_ratio * 100))))
res = {}
res["dates"] = dates
res["stats"] = stats
return res
