def get_enrolled_children_data_chart(domain,
config,
loc_level,
show_test=False):
config['month'] = datetime(*config['month'])
chart_data = AggChildHealthMonthly.objects.filter(**config).values(
'month', 'age_tranche', '%s_name' % loc_level).annotate(
valid=Sum('valid_in_month'), ).order_by('month')
if not show_test:
chart_data = apply_exclude(domain, chart_data)
chart = OrderedDict()
chart.update({'0-1 month': 0})
chart.update({'1-6 months': 0})
chart.update({'6-12 months': 0})
chart.update({'1-3 years': 0})
chart.update({'3-6 years': 0})
all = 0
best_worst = {}
for row in chart_data:
location = row['%s_name' % loc_level]
if not row['age_tranche']:
continue
age = int(row['age_tranche'])
valid = row['valid']
all += valid
chart[match_age(age)] += valid
if location in best_worst:
best_worst[location] += valid
else:
best_worst[location] = valid
return {
"chart_data": [{
"values": [{
'x': key,
'y': value,
'all': all
} for key, value in six.iteritems(chart)],
"key":
"Children (0-6 years) who are enrolled",
"strokeWidth":
2,
"classed":
"dashed",
"color":
ChartColors.BLUE
}],
"location_type":
loc_level.title()
if loc_level != LocationTypes.SUPERVISOR else 'Sector'
}
def get_enrolled_children_data_chart(domain, config, loc_level, show_test=False):
config['month'] = datetime(*config['month'])
chart_data = AggChildHealthMonthly.objects.filter(
**config
).values(
'month', 'age_tranche', '%s_name' % loc_level
).annotate(
valid=Sum('valid_in_month'),
).order_by('month')
if not show_test:
chart_data = apply_exclude(domain, chart_data)
chart = OrderedDict()
chart.update({'0-1 month': 0})
chart.update({'1-6 months': 0})
chart.update({'6-12 months': 0})
chart.update({'1-3 years': 0})
chart.update({'3-6 years': 0})
all = 0
best_worst = {}
for row in chart_data:
location = row['%s_name' % loc_level]
if not row['age_tranche']:
continue
age = int(row['age_tranche'])
valid = row['valid']
all += valid
chart[match_age(age)] += valid
if location in best_worst:
best_worst[location] += valid
else:
best_worst[location] = valid
return {
"chart_data": [
{
"values": [
{
'x': key,
'y': value,
'all': all
} for key, value in six.iteritems(chart)
],
"key": "Children (0-6 years) who are enrolled",
"strokeWidth": 2,
"classed": "dashed",
"color": ChartColors.BLUE
}
],
"location_type": loc_level.title() if loc_level != LocationTypes.SUPERVISOR else 'Sector'
}
def get_awc_report_demographics(domain, config, month, show_test=False):
selected_month = datetime(*month)
chart = AggChildHealthMonthly.objects.filter(
month=selected_month,
**config).values('age_tranche', 'aggregation_level').annotate(
valid=Sum('valid_in_month')).order_by('age_tranche')
if not show_test:
chart = apply_exclude(domain, chart)
chart_data = OrderedDict()
chart_data.update({'0-1 month': 0})
chart_data.update({'1-6 months': 0})
chart_data.update({'6-12 months': 0})
chart_data.update({'1-3 years': 0})
chart_data.update({'3-6 years': 0})
for chart_row in chart:
if chart_row['age_tranche']:
age = int(chart_row['age_tranche'])
valid = chart_row['valid']
chart_data[match_age(age)] += valid
def get_data_for(query_class, filters):
queryset = query_class.objects.filter(
**filters).values('aggregation_level').annotate(
household=Sum('cases_household'),
child_health=Sum('cases_child_health'),
child_health_all=Sum('cases_child_health_all'),
ccs_pregnant=Sum('cases_ccs_pregnant'),
ccs_pregnant_all=Sum('cases_ccs_pregnant_all'),
css_lactating=Sum('cases_ccs_lactating'),
css_lactating_all=Sum('cases_ccs_lactating_all'),
person_adolescent=(Sum('cases_person_adolescent_girls_11_14') +
Sum('cases_person_adolescent_girls_15_18')),
person_adolescent_all=(
Sum('cases_person_adolescent_girls_11_14_all') +
Sum('cases_person_adolescent_girls_15_18_all')),
person_aadhaar=Sum('cases_person_has_aadhaar'),
all_persons=Sum('cases_person_beneficiary'))
if not show_test:
queryset = apply_exclude(domain, queryset)
return queryset
yesterday = datetime.now() - relativedelta(days=1)
two_days_ago = yesterday - relativedelta(days=1)
now = datetime.utcnow()
previous_month = selected_month - relativedelta(months=1)
if selected_month.month == now.month and selected_month.year == now.year:
config['date'] = yesterday
data = get_data_for(AggAwcDailyView, config)
config['date'] = two_days_ago
prev_data = get_data_for(AggAwcDailyView, config)
frequency = 'day'
else:
config['month'] = selected_month
data = get_data_for(AggAwcMonthly, config)
config['month'] = previous_month
prev_data = get_data_for(AggAwcMonthly, config)
frequency = 'month'
return {
'chart': [{
'key':
'Children (0-6 years)',
'values': [[key, value] for key, value in chart_data.iteritems()],
"classed":
"dashed",
}],
'kpi':
[[{
'label':
_('Registered Households'),
'help_text':
_("Total number of households registered"),
'percent':
percent_increase(
'household',
data,
prev_data,
),
'color':
'green'
if percent_increase('household', data, prev_data) > 0 else 'red',
'value':
get_value(data, 'household'),
'all':
'',
'format':
'number',
'frequency':
frequency
},
{
'label':
_('Percent Adhaar-seeded Beneficiaries'),
'help_text':
_('Percentage of ICDS beneficiaries whose Adhaar identification has been captured'
),
'percent':
percent_diff('person_aadhaar', data, prev_data, 'all_persons'),
'value':
get_value(data, 'person_aadhaar'),
'all':
get_value(data, 'all_persons'),
'format':
'percent_and_div',
'frequency':
frequency
}],
[{
'label':
_('Children (0-6 years)'),
'help_text':
_('Total number of children registered between the age of 0 - 6 years'
),
'percent':
percent_increase('child_health_all', data, prev_data),
'color':
'green'
if percent_increase('child_health_all', data, prev_data) > 0 else
'red',
'value':
get_value(data, 'child_health_all'),
'all':
None,
'format':
'number',
'frequency':
frequency,
}, {
'label':
_('Children (0-6 years) enrolled for ICDS services'),
'help_text':
_(("Total number of children registered between the age of 0 - 6 years "
"and enrolled for ICDS services")),
'percent':
percent_increase('child_health', data, prev_data),
'color':
'green' if percent_increase('child_health', data, prev_data) > 0
else 'red',
'value':
get_value(data, 'child_health'),
'all':
None,
'format':
'number',
'frequency':
frequency
}],
[
{
'label':
_('Pregnant Women'),
'help_text':
_("Total number of pregnant women registered"),
'percent':
percent_increase(
'ccs_pregnant_all',
data,
prev_data,
),
'color':
'green'
if percent_increase('ccs_pregnant_all', data, prev_data) > 0
else 'red',
'value':
get_value(data, 'ccs_pregnant_all'),
'all':
'',
'format':
'number',
'frequency':
frequency
},
{
'label':
_('Pregnant Women enrolled for ICDS services'),
'help_text':
_('Total number of pregnant women registered and enrolled for ICDS services'
),
'percent':
percent_increase('ccs_pregnant', data, prev_data),
'color':
'green'
if percent_increase('ccs_pregnant', data, prev_data) > 0 else
'red',
'value':
get_value(data, 'ccs_pregnant'),
'all':
None,
'format':
'number',
'frequency':
frequency
},
],
[
{
'label':
_('Lactating Mothers'),
'help_text':
_('Total number of lactating women registered'),
'percent':
percent_increase('css_lactating_all', data, prev_data),
'color':
'green'
if percent_increase('css_lactating_all', data, prev_data) > 0
else 'red',
'value':
get_value(data, 'css_lactating_all'),
'all':
'',
'format':
'number',
'frequency':
frequency
},
{
'label':
_('Lactating Women enrolled for ICDS services'),
'help_text':
_('Total number of lactating women registered and enrolled for ICDS services'
),
'percent':
percent_increase('css_lactating', data, prev_data),
'color':
'green'
if percent_increase('css_lactating', data, prev_data) > 0 else
'red',
'value':
get_value(data, 'css_lactating'),
'all':
None,
'format':
'number',
'frequency':
frequency
},
],
[{
'label':
_('Adolescent Girls (11-18 years)'),
'help_text':
_('Total number of adolescent girls (11 - 18 years) who are registered'
),
'percent':
percent_increase(
'person_adolescent_all',
data,
prev_data,
),
'color':
'green'
if percent_increase('person_adolescent_all', data, prev_data) > 0
else 'red',
'value':
get_value(data, 'person_adolescent_all'),
'all':
'',
'format':
'number',
'frequency':
frequency
}, {
'label':
_('Adolescent Girls (11-18 years) enrolled for ICDS services'),
'help_text':
_(("Total number of adolescent girls (11 - 18 years) "
"who are registered and enrolled for ICDS services")),
'percent':
percent_increase('person_adolescent', data, prev_data),
'color':
'green'
if percent_increase('person_adolescent', data, prev_data) > 0 else
'red',
'value':
get_value(data, 'person_adolescent'),
'all':
None,
'format':
'number',
'frequency':
frequency
}]]
}
def get_awc_report_demographics(domain,
config,
now_date,
month,
show_test=False,
beta=False):
selected_month = datetime(*month)
now_date = datetime(*now_date)
chart = AggChildHealthMonthly.objects.filter(
month=selected_month,
**config).values('age_tranche', 'aggregation_level').annotate(
valid=Sum('valid_in_month')).order_by('age_tranche')
if not show_test:
chart = apply_exclude(domain, chart)
chart_data = OrderedDict()
chart_data.update({'0-1 month': 0})
chart_data.update({'1-6 months': 0})
chart_data.update({'6-12 months': 0})
chart_data.update({'1-3 years': 0})
chart_data.update({'3-6 years': 0})
for chart_row in chart:
if chart_row['age_tranche']:
age = int(chart_row['age_tranche'])
valid = chart_row['valid']
chart_data[match_age(age)] += valid
def get_data_for(query_class, filters):
queryset = query_class.objects.filter(
**filters).values('aggregation_level').annotate(
household=Sum('cases_household'),
child_health=Sum('cases_child_health'),
child_health_all=Sum('cases_child_health_all'),
ccs_pregnant=Sum('cases_ccs_pregnant'),
ccs_pregnant_all=Sum('cases_ccs_pregnant_all'),
css_lactating=Sum('cases_ccs_lactating'),
css_lactating_all=Sum('cases_ccs_lactating_all'),
person_adolescent=Sum('cases_person_adolescent_girls_11_14'),
person_adolescent_all=Sum(
'cases_person_adolescent_girls_11_14_all'),
person_aadhaar=Sum(person_has_aadhaar_column(beta)),
all_persons=Sum(person_is_beneficiary_column(beta)))
if not show_test:
queryset = apply_exclude(domain, queryset)
return queryset
yesterday = now_date - relativedelta(days=1)
two_days_ago = yesterday - relativedelta(days=1)
previous_month = selected_month - relativedelta(months=1)
if selected_month.month == now_date.month and selected_month.year == now_date.year:
config['date'] = yesterday
data = get_data_for(AggAwcDailyView, config)
config['date'] = two_days_ago
prev_data = get_data_for(AggAwcDailyView, config)
if not data:
data = prev_data
config['date'] = (two_days_ago - relativedelta(days=1)).date()
prev_data = get_data_for(AggAwcDailyView, config)
frequency = 'day'
else:
config['month'] = selected_month
data = get_data_for(AggAwcMonthly, config)
config['month'] = previous_month
prev_data = get_data_for(AggAwcMonthly, config)
frequency = 'month'
return {
'chart': [{
'key':
'Children (0-6 years)',
'values':
[[key, value] for key, value in six.iteritems(chart_data)],
"classed":
"dashed",
}],
'kpi':
[[{
'label':
_('Registered Households'),
'help_text':
_("Total number of households registered"),
'percent':
percent_increase(
'household',
data,
prev_data,
),
'color':
'green'
if percent_increase('household', data, prev_data) > 0 else 'red',
'value':
get_value(data, 'household'),
'all':
'',
'format':
'number',
'frequency':
frequency
},
{
'label':
_('Percent Aadhaar-seeded Beneficiaries'),
'help_text':
_('Of the total number of ICDS beneficiaries, the percentage whose Adhaar identification '
'has been captured. '),
'percent':
percent_diff('person_aadhaar', data, prev_data, 'all_persons'),
'color':
'green' if percent_diff('person_aadhaar', data, prev_data,
'all_persons') > 0 else 'red',
'value':
get_value(data, 'person_aadhaar'),
'all':
get_value(data, 'all_persons'),
'format':
'percent_and_div',
'frequency':
frequency
}],
[{
'label':
_('Percent children (0-6 years) enrolled for Anganwadi Services'),
'help_text':
_('Of the total number of children between 0-6 years, the percentage '
'of children who are enrolled for Anganwadi Services'),
'percent':
percent_diff('child_health', data, prev_data, 'child_health_all'),
'color':
'green' if percent_diff('child_health_all', data, prev_data,
'child_health_all') > 0 else 'red',
'value':
get_value(data, 'child_health'),
'all':
get_value(data, 'child_health_all'),
'format':
'percent_and_div',
'frequency':
frequency,
}, {
'label':
_('Percent pregnant women enrolled for Anganwadi Services'),
'help_text':
_('Of the total number of pregnant women, the percentage of pregnant '
'women enrolled for Anganwadi Services'),
'percent':
percent_diff('ccs_pregnant', data, prev_data, 'ccs_pregnant_all'),
'color':
'green' if percent_diff('ccs_pregnant', data, prev_data,
'ccs_pregnant_all') > 0 else 'red',
'value':
get_value(data, 'ccs_pregnant'),
'all':
get_value(data, 'ccs_pregnant_all'),
'format':
'percent_and_div',
'frequency':
frequency
}],
[{
'label':
_('Percent lactating women enrolled for Anganwadi Services'),
'help_text':
_('Of the total number of lactating women, the percentage of '
'lactating women enrolled for Anganwadi Services'),
'percent':
percent_diff('css_lactating', data, prev_data,
'css_lactating_all'),
'color':
'green' if percent_diff('css_lactating', data, prev_data,
'css_lactating_all') > 0 else 'red',
'value':
get_value(data, 'css_lactating'),
'all':
get_value(data, 'css_lactating_all'),
'format':
'percent_and_div',
'frequency':
frequency
}, {
'label':
_('Percent adolescent girls (11-14 years) enrolled for Anganwadi Services'
),
'help_text':
_(("Of the total number of adolescent girls (aged 11-14 years), the percentage "
"of girls enrolled for Anganwadi Services")),
'percent':
percent_diff('person_adolescent', data, prev_data,
'person_adolescent_all'),
'color':
'green' if percent_diff('person_adolescent', data, prev_data,
'person_adolescent_all') > 0 else 'red',
'value':
get_value(data, 'person_adolescent'),
'all':
get_value(data, 'person_adolescent_all'),
'format':
'percent_and_div',
'frequency':
frequency
}]]
}
