def get_prevalence_of_undernutrition_data_chart(domain,
config,
loc_level,
show_test=False,
icds_features_flag=False):
month = datetime(*config['month'])
three_before = datetime(*config['month']) - relativedelta(months=3)
config['month__range'] = (three_before, month)
del config['month']
if config['aggregation_level'] >= AggregationLevels.SUPERVISOR:
chm_filter = get_filters_from_config_for_chart_view(config)
chm_queryset = ChildHealthMonthlyView.objects.filter(**chm_filter)
else:
chm_queryset = AggChildHealthMonthly.objects.filter(**config)
chart_data = chm_queryset.values('month', '%s_name' % loc_level).annotate(
moderately_underweight=Sum('nutrition_status_moderately_underweight'),
normal=Sum('nutrition_status_normal'),
severely_underweight=Sum('nutrition_status_severely_underweight'),
weighed=Sum('nutrition_status_weighed'),
total=Sum('wer_eligible'),
).order_by('month')
if not show_test:
chart_data = apply_exclude(domain, chart_data)
if 'age_tranche' not in config:
chart_data = chart_data.filter(age_tranche__lt=72)
data = {
'peach': OrderedDict(),
'orange': OrderedDict(),
'red': OrderedDict()
}
dates = [dt for dt in rrule(MONTHLY, dtstart=three_before, until=month)]
for date in dates:
miliseconds = int(date.strftime("%s")) * 1000
data['peach'][miliseconds] = {'y': 0, 'weighed': 0, 'unweighed': 0}
data['orange'][miliseconds] = {'y': 0, 'weighed': 0, 'unweighed': 0}
data['red'][miliseconds] = {'y': 0, 'weighed': 0, 'unweighed': 0}
best_worst = {}
if 'month' not in config:
config['month'] = month
location_launched_status = get_location_launched_status(config, loc_level)
for row in chart_data:
if location_launched_status:
launched_status = location_launched_status.get(row['%s_name' %
loc_level])
if launched_status is None or launched_status <= 0:
continue
date = row['month']
weighed = row['weighed'] or 0
location = row['%s_name' % loc_level]
severely_underweight = row['severely_underweight'] or 0
moderately_underweight = row['moderately_underweight'] or 0
total = row['total'] or 0
normal = row['normal'] or 0
underweight = (moderately_underweight +
severely_underweight) * 100 / float(weighed or 1)
best_worst[location] = underweight
date_in_miliseconds = int(date.strftime("%s")) * 1000
data['peach'][date_in_miliseconds]['y'] += normal
data['peach'][date_in_miliseconds]['unweighed'] += (total - weighed)
data['peach'][date_in_miliseconds]['weighed'] += weighed
data['orange'][date_in_miliseconds]['y'] += moderately_underweight
data['orange'][date_in_miliseconds]['unweighed'] += (total - weighed)
data['orange'][date_in_miliseconds]['weighed'] += weighed
data['red'][date_in_miliseconds]['y'] += severely_underweight
data['red'][date_in_miliseconds]['unweighed'] += (total - weighed)
data['red'][date_in_miliseconds]['weighed'] += weighed
all_locations = [{
'loc_name': key,
'percent': value
} for key, value in best_worst.items()]
all_locations_sorted_by_name = sorted(all_locations,
key=lambda x: x['loc_name'])
all_locations_sorted_by_percent_and_name = sorted(
all_locations_sorted_by_name, key=lambda x: x['percent'])
return {
"chart_data": [{
"values": [{
'x': key,
'y': value['y'] / float(value['weighed'] or 1),
'weighed': value['weighed'],
'unweighed': value['unweighed'],
} for key, value in data['peach'].items()],
"key":
"% Normal",
"strokeWidth":
2,
"classed":
"dashed",
"color":
ChartColors.PINK
}, {
"values": [{
'x': key,
'y': value['y'] / float(value['weighed'] or 1),
'weighed': value['weighed'],
'unweighed': value['unweighed'],
} for key, value in data['orange'].items()],
"key":
"% Moderately Underweight (-2 SD)",
"strokeWidth":
2,
"classed":
"dashed",
"color":
ChartColors.ORANGE
}, {
"values": [{
'x': key,
'y': value['y'] / float(value['weighed'] or 1),
'weighed': value['weighed'],
'unweighed': value['unweighed'],
} for key, value in data['red'].items()],
"key":
"% Severely Underweight (-3 SD) ",
"strokeWidth":
2,
"classed":
"dashed",
"color":
ChartColors.RED
}],
"all_locations":
all_locations_sorted_by_percent_and_name,
"top_five":
all_locations_sorted_by_percent_and_name[:5],
"bottom_five":
all_locations_sorted_by_percent_and_name[-5:],
"location_type":
loc_level.title()
if loc_level != LocationTypes.SUPERVISOR else 'Sector'
}
def get_prevalence_of_severe_data_chart(domain,
config,
loc_level,
show_test=False,
icds_feature_flag=False):
month = datetime(*config['month'])
three_before = datetime(*config['month']) - relativedelta(months=3)
config['month__range'] = (three_before, month)
del config['month']
# using child health monthly while querying for sector level due to performance issues
if icds_feature_flag and config[
'aggregation_level'] >= AggregationLevels.SUPERVISOR:
chm_filter = get_filters_from_config_for_chart_view(config)
chm_queryset = ChildHealthMonthlyView.objects.filter(**chm_filter)
else:
chm_queryset = AggChildHealthMonthly.objects.filter(**config)
chart_data = chm_queryset.values('month', '%s_name' % loc_level).annotate(
moderate=Sum(wasting_moderate_column(icds_feature_flag)),
severe=Sum(wasting_severe_column(icds_feature_flag)),
normal=Sum(wasting_normal_column(icds_feature_flag)),
total_height_eligible=Sum('height_eligible'),
total_weighed=Sum('nutrition_status_weighed'),
total_measured=Sum(wfh_recorded_in_month_column(icds_feature_flag)),
).order_by('month')
if not show_test:
chart_data = apply_exclude(domain, chart_data)
if 'age_tranche' not in config:
chart_data = chart_data.filter(age_tranche__lt=72)
data = {
'red': OrderedDict(),
'orange': OrderedDict(),
'peach': OrderedDict()
}
dates = [dt for dt in rrule(MONTHLY, dtstart=three_before, until=month)]
for date in dates:
miliseconds = int(date.strftime("%s")) * 1000
data['red'][miliseconds] = {
'y': 0,
'total_weighed': 0,
'total_measured': 0,
'total_height_eligible': 0
}
data['orange'][miliseconds] = {
'y': 0,
'total_weighed': 0,
'total_measured': 0,
'total_height_eligible': 0
}
data['peach'][miliseconds] = {
'y': 0,
'total_weighed': 0,
'total_measured': 0,
'total_height_eligible': 0
}
best_worst = {}
if icds_feature_flag:
if 'month' not in config:
config['month'] = month
location_launched_status = get_location_launched_status(
config, loc_level)
else:
location_launched_status = None
for row in chart_data:
if location_launched_status:
launched_status = location_launched_status.get(row['%s_name' %
loc_level])
if launched_status is None or launched_status <= 0:
continue
date = row['month']
total_weighed = row['total_weighed'] or 0
total_measured = row['total_measured'] or 0
total_height_eligible = row['total_height_eligible'] or 0
location = row['%s_name' % loc_level]
severe = row['severe'] or 0
moderate = row['moderate'] or 0
normal = row['normal'] or 0
underweight = moderate + severe
best_worst[location] = underweight * 100 / float(total_measured or 1)
date_in_miliseconds = int(date.strftime("%s")) * 1000
data['peach'][date_in_miliseconds]['y'] += normal
data['peach'][date_in_miliseconds]['total_weighed'] += total_weighed
data['peach'][date_in_miliseconds]['total_measured'] += total_measured
data['peach'][date_in_miliseconds][
'total_height_eligible'] += total_height_eligible
data['orange'][date_in_miliseconds]['y'] += moderate
data['orange'][date_in_miliseconds]['total_weighed'] += total_weighed
data['orange'][date_in_miliseconds]['total_measured'] += total_measured
data['orange'][date_in_miliseconds][
'total_height_eligible'] += total_height_eligible
data['red'][date_in_miliseconds]['y'] += severe
data['red'][date_in_miliseconds]['total_weighed'] += total_weighed
data['red'][date_in_miliseconds]['total_measured'] += total_measured
data['red'][date_in_miliseconds][
'total_height_eligible'] += total_height_eligible
top_locations = sorted([
dict(loc_name=key, percent=value) for key, value in best_worst.items()
],
key=lambda x: (x['percent'], x['loc_name']))
return {
"chart_data": [{
"values": [{
'x': key,
'y': value['y'] / float(value['total_measured'] or 1),
'total_weighed': value['total_weighed'],
'total_measured': value['total_measured'],
'total_height_eligible': value['total_height_eligible']
} for key, value in data['peach'].items()],
"key":
"% normal",
"strokeWidth":
2,
"classed":
"dashed",
"color":
ChartColors.PINK
}, {
"values": [{
'x': key,
'y': value['y'] / float(value['total_measured'] or 1),
'total_weighed': value['total_weighed'],
'total_measured': value['total_measured'],
'total_height_eligible': value['total_height_eligible']
} for key, value in data['orange'].items()],
"key":
"% moderately wasted (moderate acute malnutrition)",
"strokeWidth":
2,
"classed":
"dashed",
"color":
ChartColors.ORANGE
}, {
"values": [{
'x': key,
'y': value['y'] / float(value['total_measured'] or 1),
'total_weighed': value['total_weighed'],
'total_measured': value['total_measured'],
'total_height_eligible': value['total_height_eligible']
} for key, value in data['red'].items()],
"key":
"% severely wasted (severe acute malnutrition)",
"strokeWidth":
2,
"classed":
"dashed",
"color":
ChartColors.RED
}],
"all_locations":
top_locations,
"top_five":
top_locations[:5],
"bottom_five":
top_locations[-5:],
"location_type":
loc_level.title()
if loc_level != LocationTypes.SUPERVISOR else 'Sector'
}
def get_early_initiation_breastfeeding_chart(domain, config, loc_level, show_test=False, icds_features_flag=False):
month = datetime(*config['month'])
three_before = datetime(*config['month']) - relativedelta(months=3)
config['month__range'] = (three_before, month)
del config['month']
# using child health monthly while querying for sector level due to performance issues
if icds_features_flag and config['aggregation_level'] >= AggregationLevels.SUPERVISOR:
chm_filter = get_filters_from_config_for_chart_view(config)
chm_queryset = ChildHealthMonthlyView.objects.filter(**chm_filter)
else:
chm_queryset = AggChildHealthMonthly.objects.filter(**config)
chart_data = chm_queryset.values(
'month', '%s_name' % loc_level
).annotate(
birth=Sum('bf_at_birth'),
in_month=Sum('born_in_month'),
).order_by('month')
if not show_test:
chart_data = apply_exclude(domain, chart_data)
data = {
'blue': OrderedDict()
}
dates = [dt for dt in rrule(MONTHLY, dtstart=three_before, until=month)]
for date in dates:
miliseconds = int(date.strftime("%s")) * 1000
data['blue'][miliseconds] = {'y': 0, 'all': 0, 'birth': 0}
best_worst = {}
if icds_features_flag:
if 'month' not in config:
config['month'] = month
location_launched_status = get_location_launched_status(config, loc_level)
else:
location_launched_status = None
for row in chart_data:
if location_launched_status:
launched_status = location_launched_status.get(row['%s_name' % loc_level])
if launched_status is None or launched_status <= 0:
continue
date = row['month']
in_month = row['in_month']
location = row['%s_name' % loc_level]
birth = row['birth']
best_worst[location] = (birth or 0) * 100 / float(in_month or 1)
date_in_miliseconds = int(date.strftime("%s")) * 1000
data_for_month = data['blue'][date_in_miliseconds]
data_for_month['all'] += in_month
data_for_month['birth'] += birth
data_for_month['y'] = data_for_month['birth'] / float(data_for_month['all'] or 1)
all_locations = [
{
'loc_name': key,
'percent': val
}
for key, val in best_worst.items()
]
all_locations_sorted_by_name = sorted(all_locations, key=lambda x: x['loc_name'])
all_locations_sorted_by_percent_and_name = sorted(
all_locations_sorted_by_name, key=lambda x: x['percent'], reverse=True)
return {
"chart_data": [
{
"values": [
{
'x': key,
'y': val['y'],
'all': val['all'],
'birth': val['birth']
} for key, val in data['blue'].items()
],
"key": "% Early Initiation of Breastfeeding",
"strokeWidth": 2,
"classed": "dashed",
"color": ChartColors.BLUE
}
],
"all_locations": all_locations_sorted_by_percent_and_name,
"top_five": all_locations_sorted_by_percent_and_name[:5],
"bottom_five": all_locations_sorted_by_percent_and_name[-5:],
"location_type": loc_level.title() if loc_level != LocationTypes.SUPERVISOR else 'Sector'
}
def get_immunization_coverage_data_chart(domain,
config,
loc_level,
show_test=False,
icds_features_flag=False):
month = datetime(*config['month'])
three_before = datetime(*config['month']) - relativedelta(months=3)
config['month__range'] = (three_before, month)
# Retrieving children of age 1-2 years
config['age_tranche__lte'] = '24'
del config['month']
# using child health monthly while querying for sector level due to performance issues
if config['aggregation_level'] >= AggregationLevels.SUPERVISOR:
chm_filter = get_filters_from_config_for_chart_view(config)
chm_queryset = ChildHealthMonthlyView.objects.filter(**chm_filter)
else:
chm_queryset = AggChildHealthMonthly.objects.filter(**config)
chart_data = chm_queryset.values('month', '%s_name' % loc_level).annotate(
in_month=Sum('fully_immunized_on_time') + Sum('fully_immunized_late'),
eligible=Sum('fully_immunized_eligible'),
).order_by('month')
if not show_test:
chart_data = apply_exclude(domain, chart_data)
data = {
'blue': OrderedDict(),
}
dates = [dt for dt in rrule(MONTHLY, dtstart=three_before, until=month)]
for date in dates:
miliseconds = int(date.strftime("%s")) * 1000
data['blue'][miliseconds] = {'y': 0, 'all': 0, 'in_month': 0}
best_worst = defaultdict(lambda: {'in_month': 0, 'all': 0})
if 'month' not in config:
config['month'] = month
location_launched_status = get_location_launched_status(config, loc_level)
for row in chart_data:
if location_launched_status:
launched_status = location_launched_status.get(row['%s_name' %
loc_level])
if launched_status is None or launched_status <= 0:
continue
date = row['month']
in_month = row['in_month']
location = row['%s_name' % loc_level]
valid = row['eligible']
best_worst[location]['in_month'] = in_month
best_worst[location]['all'] = (valid or 0)
date_in_miliseconds = int(date.strftime("%s")) * 1000
data_for_month = data['blue'][date_in_miliseconds]
data_for_month['all'] += valid
data_for_month['in_month'] += in_month
data_for_month['y'] = data_for_month['in_month'] / float(
data_for_month['all'] or 1)
all_locations = [{
'loc_name':
key,
'percent': (value['in_month'] * 100) / float(value['all'] or 1)
} for key, value in best_worst.items()]
all_locations_sorted_by_name = sorted(all_locations,
key=lambda x: x['loc_name'])
all_locations_sorted_by_percent_and_name = sorted(
all_locations_sorted_by_name, key=lambda x: x['percent'], reverse=True)
return {
"chart_data": [{
"values": [{
'x': key,
'y': value['y'],
'all': value['all'],
'in_month': value['in_month']
} for key, value in data['blue'].items()],
"key":
"% Children between 1-2 years old who received complete immunizations by 1 year",
"strokeWidth":
2,
"classed":
"dashed",
"color":
ChartColors.BLUE
}],
"all_locations":
all_locations_sorted_by_percent_and_name,
"top_five":
all_locations_sorted_by_percent_and_name[:5],
"bottom_five":
all_locations_sorted_by_percent_and_name[-5:],
"location_type":
loc_level.title()
if loc_level != LocationTypes.SUPERVISOR else 'Sector'
}
