def display_maternal(scores):
fields = [
f for f in MaternalCare._meta.get_fields()
if f.verbose_name in datapoints.maternal
]
for f in fields:
point = str(f).strip().split(".")[2]
data_point = maternal.get_maternal_care(point)
score = c.get_correlation_score(
c.make_variables(records[0], data_point))
scores.append({
'category':
'Weight for Age - Underweight and Severely Underweight',
'source': 'Maternal Care',
'field': f.verbose_name,
'score': score,
'report': 'City Maternal Care',
'variables': c.make_variables(records[0], data_point),
'remark': get_correlation_remark(score)
})
for f in fields:
point = str(f).strip().split(".")[2]
data_point = maternal.get_maternal_care(point)
score = c.get_correlation_score(
c.make_variables(records[1], data_point))
scores.append({
'category': 'Height for Age - Stunted and Severely Stunted',
'source': 'Maternal Care',
'field': f.verbose_name,
'score': score,
'report': 'City Maternal Care',
'variables': c.make_variables(records[1], data_point),
'remark': get_correlation_remark(score)
})
for f in fields:
point = str(f).strip().split(".")[2]
data_point = maternal.get_maternal_care(point)
score = c.get_correlation_score(
c.make_variables(records[2], data_point))
scores.append({
'category':
'Weight for Height/Length - Wasted and Severely Wasted',
'source': 'Maternal Care',
'field': f.verbose_name,
'score': score,
'report': 'City Maternal Care',
'variables': c.make_variables(records[2], data_point),
'remark': get_correlation_remark(score)
})
return scores
def display_micronutrient(scores):
fields = [
f for f in ChildCare._meta.get_fields()
if f.verbose_name in datapoints.micronutrient
]
for f in fields:
point = str(f).strip().split(".")[2]
data_point = child_care.get_fhsis(ChildCare, point, None)
score = c.get_correlation_score(
c.make_variables(records[0], data_point))
scores.append({
'category':
'Weight for Age - Underweight and Severely Underweight',
'source': 'Child Care',
'field': f.verbose_name,
'score': score,
'report': 'Micronutrient Supplementation',
'variables': c.make_variables(records[0], data_point),
'remark': get_correlation_remark(score)
})
for f in fields:
point = str(f).strip().split(".")[2]
data_point = child_care.get_fhsis(ChildCare, point, None)
score = c.get_correlation_score(
c.make_variables(records[1], data_point))
scores.append({
'category': 'Height for Age - Stunted and Severely Stunted',
'source': 'Child Care',
'field': f.verbose_name,
'score': score,
'report': 'Micronutrient Supplementation',
'variables': c.make_variables(records[1], data_point),
'remark': get_correlation_remark(score)
})
for f in fields:
point = str(f).strip().split(".")[2]
data_point = child_care.get_fhsis(ChildCare, point, None)
score = c.get_correlation_score(
c.make_variables(records[2], data_point))
scores.append({
'category':
'Weight for Height/Length - Wasted and Severely Wasted',
'source': 'Child Care',
'field': f.verbose_name,
'score': score,
'report': 'Micronutrient Supplementation',
'variables': c.make_variables(records[2], data_point),
'remark': get_correlation_remark(score)
})
return scores
def get_maternal_revised():
scores = []
fields = [
f for f in MaternalCare._meta.get_fields()
if f.verbose_name in datapoints.maternal
]
for field in fields:
point = str(field).strip().split(".")[2]
data_point = maternal.get_maternal_care(point)
wfa_score = float(
c.get_correlation_score(c.make_variables(records[0], data_point)))
hfa_score = float(
c.get_correlation_score(c.make_variables(records[1], data_point)))
wfhl_score = float(
c.get_correlation_score(c.make_variables(records[2], data_point)))
scores.append({
'source':
'Maternal Care',
'field':
field.verbose_name,
'data': [{
'category':
'Weight for Age - Underweight and Severely Underweight',
'score': wfa_score,
'remark': get_correlation_remark(wfa_score),
'variables': c.make_variables(records[0], data_point)
}, {
'category': 'Height for Age - Stunted and Severely Stunted',
'score': hfa_score,
'remark': get_correlation_remark(hfa_score),
'variables': c.make_variables(records[1], data_point)
}, {
'category':
'Weight for Height/Length - Wasted and Severely Wasted',
'score': wfhl_score,
'remark': get_correlation_remark(wfhl_score),
'variables': c.make_variables(records[2], data_point)
}]
})
return scores
def display_socioeconomic(scores):
fields = socioeconomic.fields
for f in fields:
data_point = socioeconomic.get_socioeconomic(f)
score = c.get_correlation_score(
c.make_variables(records[0], data_point))
scores.append({
'category':
'Weight for Age - Underweight and Severely Underweight',
'source': 'Family Profile',
'field': f,
'score': score,
'report': 'Socioeconomic',
'variables': c.make_variables(records[0], data_point),
'remark': get_correlation_remark(score)
})
for f in fields:
data_point = socioeconomic.get_socioeconomic(f)
score = c.get_correlation_score(
c.make_variables(records[1], data_point))
scores.append({
'category': 'Height for Age - Stunted and Severely Stunted',
'source': 'Family Profile',
'field': f,
'score': score,
'report': 'Socioeconomic',
'variables': c.make_variables(records[1], data_point),
'remark': get_correlation_remark(score)
})
for f in fields:
data_point = socioeconomic.get_socioeconomic(f)
score = c.get_correlation_score(
c.make_variables(records[2], data_point))
scores.append({
'category':
'Weight for Height/Length - Wasted and Severely Wasted',
'source': 'Family Profile',
'field': f,
'score': score,
'report': 'Socioeconomic',
'variables': c.make_variables(records[2], data_point),
'remark': get_correlation_remark(score)
})
data_point = socioeconomic.get_members_data()
score = c.get_correlation_score(c.make_variables(records[0], data_point))
scores.append({
'category': 'Weight for Age - Underweight and Severely Underweight',
'source': 'Family Profile',
'field': 'Total Members',
'score': score,
'report': 'Socioeconomic',
'variables': c.make_variables(records[0], data_point),
'remark': get_correlation_remark(score)
})
score = c.get_correlation_score(c.make_variables(records[1], data_point))
scores.append({
'category': 'Height for Age - Stunted and Severely Stunted',
'source': 'Family Profile',
'field': 'Total Members',
'score': score,
'report': 'Socioeconomic',
'variables': c.make_variables(records[1], data_point),
'remark': get_correlation_remark(score)
})
score = c.get_correlation_score(c.make_variables(records[2], data_point))
scores.append({
'category': 'Weight for Height/Length - Wasted and Severely Wasted',
'source': 'Family Profile',
'field': 'Total Members',
'score': score,
'report': 'Socioeconomic',
'variables': c.make_variables(records[2], data_point),
'remark': get_correlation_remark(score)
})
# education
attainments = datapoints.educational_attainment_for_r
for a in attainments:
data_point = socioeconomic.get_educational_attainment(a)
score = c.get_correlation_score(
c.make_variables(records[0], data_point))
scores.append({
'category':
'Weight for Age - Underweight and Severely Underweight',
'source': 'Family Profile',
'field': a,
'score': score,
'report': 'Socioeconomic',
'variables': c.make_variables(records[0], data_point),
'remark': get_correlation_remark(score)
})
for a in attainments:
data_point = socioeconomic.get_educational_attainment(a)
score = c.get_correlation_score(
c.make_variables(records[1], data_point))
scores.append({
'category': 'Height for Age - Stunted and Severely Stunted',
'source': 'Family Profile',
'field': a,
'score': score,
'report': 'Socioeconomic',
'variables': c.make_variables(records[1], data_point),
'remark': get_correlation_remark(score)
})
for a in attainments:
data_point = socioeconomic.get_educational_attainment(a)
score = c.get_correlation_score(
c.make_variables(records[2], data_point))
scores.append({
'category':
'Weight for Height/Length - Wasted and Severely Wasted',
'source': 'Family Profile',
'field': a,
'score': score,
'report': 'Socioeconomic',
'variables': c.make_variables(records[2], data_point),
'remark': get_correlation_remark(score)
})
# toilet type
toilets = datapoints.toilet_type
for t in toilets:
data_point = socioeconomic.get_toilet_type(t)
score = c.get_correlation_score(
c.make_variables(records[0], data_point))
scores.append({
'category':
'Weight for Age - Underweight and Severely Underweight',
'source': 'Family Profile',
'field': t,
'score': score,
'report': 'Socioeconomic',
'variables': c.make_variables(records[0], data_point),
'remark': get_correlation_remark(score)
})
for t in toilets:
data_point = socioeconomic.get_toilet_type(t)
score = c.get_correlation_score(
c.make_variables(records[1], data_point))
scores.append({
'category': 'Height for Age - Stunted and Severely Stunted',
'source': 'Family Profile',
'field': t,
'score': score,
'report': 'Socioeconomic',
'variables': c.make_variables(records[1], data_point),
'remark': get_correlation_remark(score)
})
for t in toilets:
data_point = socioeconomic.get_toilet_type(t)
score = c.get_correlation_score(
c.make_variables(records[2], data_point))
scores.append({
'category':
'Weight for Height/Length - Wasted and Severely Wasted',
'source': 'Family Profile',
'field': t,
'score': score,
'report': 'Socioeconomic',
'variables': c.make_variables(records[2], data_point),
'remark': get_correlation_remark(score)
})
# food production
ways = datapoints.food_production
for w in ways:
data_point = socioeconomic.get_food_production(w)
score = c.get_correlation_score(
c.make_variables(records[0], data_point))
scores.append({
'category':
'Weight for Age - Underweight and Severely Underweight',
'source': 'Family Profile',
'field': w,
'score': score,
'report': 'Socioeconomic',
'variables': c.make_variables(records[0], data_point),
'remark': get_correlation_remark(score)
})
for w in ways:
data_point = socioeconomic.get_food_production(w)
score = c.get_correlation_score(
c.make_variables(records[1], data_point))
scores.append({
'category': 'Height for Age - Stunted and Severely Stunted',
'source': 'Family Profile',
'field': w,
'score': score,
'report': 'Socioeconomic',
'variables': c.make_variables(records[1], data_point),
'remark': get_correlation_remark(score)
})
for w in ways:
data_point = socioeconomic.get_food_production(w)
score = c.get_correlation_score(
c.make_variables(records[2], data_point))
scores.append({
'category':
'Weight for Height/Length - Wasted and Severely Wasted',
'source': 'Family Profile',
'field': w,
'score': score,
'report': 'Socioeconomic',
'variables': c.make_variables(records[2], data_point),
'remark': get_correlation_remark(score)
})
# WATER SOURCES
ws = datapoints.water_sources
for w in ws:
data_point = socioeconomic.get_water_source(w)
score = c.get_correlation_score(
c.make_variables(records[0], data_point))
scores.append({
'category':
'Weight for Age - Underweight and Severely Underweight',
'source': 'Family Profile',
'field': w,
'score': score,
'report': 'Socioeconomic',
'variables': c.make_variables(records[0], data_point),
'remark': get_correlation_remark(score)
})
for w in ws:
data_point = socioeconomic.get_water_source(w)
score = c.get_correlation_score(
c.make_variables(records[1], data_point))
scores.append({
'category': 'Height for Age - Stunted and Severely Stunted',
'source': 'Family Profile',
'field': w,
'score': score,
'report': 'Socioeconomic',
'variables': c.make_variables(records[1], data_point),
'remark': get_correlation_remark(score)
})
for w in ws:
data_point = socioeconomic.get_water_source(w)
score = c.get_correlation_score(
c.make_variables(records[2], data_point))
scores.append({
'category':
'Weight for Height/Length - Wasted and Severely Wasted',
'source': 'Family Profile',
'field': w,
'score': score,
'report': 'Socioeconomic',
'variables': c.make_variables(records[2], data_point),
'remark': get_correlation_remark(score)
})
return scores
def display_child_care(scores):
fields = [
f for f in ChildCare._meta.get_fields()
if f.verbose_name in datapoints.child_care
]
immunization_fields = [
f for f in Immunization._meta.get_fields()
if f.verbose_name in datapoints.immunizations
]
malaria_fields = [
f for f in Malaria._meta.get_fields()
if f.verbose_name in datapoints.malaria
]
tb_fields = [
f for f in Tuberculosis._meta.get_fields()
if f.verbose_name in datapoints.tuberculosis
]
# original child care
for f in fields:
point = str(f).strip().split(".")[2]
data_point = child_care.get_fhsis(ChildCare, point, None)
score = c.get_correlation_score(
c.make_variables(records[0], data_point))
scores.append({
'category':
'Weight for Age - Underweight and Severely Underweight',
'source': 'Child Care',
'field': f.verbose_name,
'score': score,
'report': 'City Children Care',
'variables': c.make_variables(records[0], data_point),
'remark': get_correlation_remark(score)
})
for f in fields:
point = str(f).strip().split(".")[2]
data_point = child_care.get_fhsis(ChildCare, point, None)
score = c.get_correlation_score(
c.make_variables(records[1], data_point))
scores.append({
'category': 'Height for Age - Stunted and Severely Stunted',
'source': 'Child Care',
'field': f.verbose_name,
'score': score,
'report': 'City Children Care',
'variables': c.make_variables(records[1], data_point),
'remark': get_correlation_remark(score)
})
for f in fields:
point = str(f).strip().split(".")[2]
data_point = child_care.get_fhsis(ChildCare, point, None)
score = c.get_correlation_score(
c.make_variables(records[2], data_point))
scores.append({
'category':
'Weight for Height/Length - Wasted and Severely Wasted',
'source': 'Child Care',
'field': f.verbose_name,
'score': score,
'report': 'City Children Care',
'variables': c.make_variables(records[2], data_point),
'remark': get_correlation_remark(score)
})
# immunizations
for f in immunization_fields:
point = str(f).strip().split(".")[2]
data_point = child_care.get_fhsis(Immunization, point, None)
score = c.get_correlation_score(
c.make_variables(records[0], data_point))
scores.append({
'category':
'Weight for Age - Underweight and Severely Underweight',
'source': 'Immunization',
'field': f.verbose_name,
'score': score,
'report': 'City Children Care',
'variables': c.make_variables(records[0], data_point),
'remark': get_correlation_remark(score)
})
for f in immunization_fields:
point = str(f).strip().split(".")[2]
data_point = child_care.get_fhsis(Immunization, point, None)
score = c.get_correlation_score(
c.make_variables(records[1], data_point))
scores.append({
'category': 'Height for Age - Stunted and Severely Stunted',
'source': 'Immunization',
'field': f.verbose_name,
'score': score,
'report': 'City Children Care',
'variables': c.make_variables(records[1], data_point),
'remark': get_correlation_remark(score)
})
for f in immunization_fields:
point = str(f).strip().split(".")[2]
data_point = child_care.get_fhsis(Immunization, point, None)
score = c.get_correlation_score(
c.make_variables(records[2], data_point))
scores.append({
'category':
'Weight for Height/Length - Wasted and Severely Wasted',
'source': 'Immunization',
'field': f.verbose_name,
'score': score,
'report': 'City Children Care',
'variables': c.make_variables(records[2], data_point),
'remark': get_correlation_remark(score)
})
# malaria
for f in malaria_fields:
point = str(f).strip().split(".")[2]
data_point = child_care.get_fhsis(Malaria, point, None)
score = c.get_correlation_score(
c.make_variables(records[0], data_point))
scores.append({
'category':
'Weight for Age - Underweight and Severely Underweight',
'source': 'Malaria',
'field': f.verbose_name,
'score': score,
'report': 'City Children Care',
'variables': c.make_variables(records[0], data_point),
'remark': get_correlation_remark(score)
})
for f in malaria_fields:
point = str(f).strip().split(".")[2]
data_point = child_care.get_fhsis(Malaria, point, None)
score = c.get_correlation_score(
c.make_variables(records[1], data_point))
scores.append({
'category': 'Height for Age - Stunted and Severely Stunted',
'source': 'Malaria',
'field': f.verbose_name,
'score': score,
'report': 'City Children Care',
'variables': c.make_variables(records[1], data_point),
'remark': get_correlation_remark(score)
})
for f in malaria_fields:
point = str(f).strip().split(".")[2]
data_point = child_care.get_fhsis(Malaria, point, None)
score = c.get_correlation_score(
c.make_variables(records[2], data_point))
scores.append({
'category':
'Weight for Height/Length - Wasted and Severely Wasted',
'source': 'Malaria',
'field': f.verbose_name,
'score': score,
'report': 'City Children Care',
'variables': c.make_variables(records[2], data_point),
'remark': get_correlation_remark(score)
})
# tb
for f in tb_fields:
point = str(f).strip().split(".")[2]
data_point = child_care.get_fhsis(Tuberculosis, point, None)
score = c.get_correlation_score(
c.make_variables(records[0], data_point))
scores.append({
'category':
'Weight for Age - Underweight and Severely Underweight',
'source': 'Tuberculosis',
'field': f.verbose_name,
'score': score,
'report': 'City Children Care',
'variables': c.make_variables(records[0], data_point),
'remark': get_correlation_remark(score)
})
for f in tb_fields:
point = str(f).strip().split(".")[2]
data_point = child_care.get_fhsis(Tuberculosis, point, None)
score = c.get_correlation_score(
c.make_variables(records[1], data_point))
scores.append({
'category': 'Height for Age - Stunted and Severely Stunted',
'source': 'Tuberculosis',
'field': f.verbose_name,
'score': score,
'report': 'City Children Care',
'variables': c.make_variables(records[1], data_point),
'remark': get_correlation_remark(score)
})
for f in tb_fields:
point = str(f).strip().split(".")[2]
data_point = child_care.get_fhsis(Tuberculosis, point, None)
score = c.get_correlation_score(
c.make_variables(records[2], data_point))
scores.append({
'category':
'Weight for Height/Length - Wasted and Severely Wasted',
'source': 'Tuberculosis',
'field': f.verbose_name,
'score': score,
'report': 'City Children Care',
'variables': c.make_variables(records[2], data_point),
'remark': get_correlation_remark(score)
})
return scores
def get_socioeconomic_revised():
scores = []
fields = socioeconomic.fields
for field in fields:
data_point = socioeconomic.get_socioeconomic(field)
wfa_score = float(
c.get_correlation_score(c.make_variables(records[0], data_point)))
hfa_score = float(
c.get_correlation_score(c.make_variables(records[1], data_point)))
wfhl_score = float(
c.get_correlation_score(c.make_variables(records[2], data_point)))
scores.append({
'source':
'Family Profile',
'field':
field,
'data': [{
'category':
'Weight for Age - Underweight and Severely Underweight',
'score': wfa_score,
'remark': get_correlation_remark(wfa_score),
'variables': c.make_variables(records[0], data_point)
}, {
'category': 'Height for Age - Stunted and Severely Stunted',
'score': hfa_score,
'remark': get_correlation_remark(hfa_score),
'variables': c.make_variables(records[1], data_point)
}, {
'category':
'Weight for Height/Length - Wasted and Severely Wasted',
'score': wfhl_score,
'remark': get_correlation_remark(wfhl_score),
'variables': c.make_variables(records[2], data_point)
}]
})
# total members
data_point = socioeconomic.get_members_data()
wfa_score = float(
c.get_correlation_score(c.make_variables(records[0], data_point)))
hfa_score = float(
c.get_correlation_score(c.make_variables(records[1], data_point)))
wfhl_score = float(
c.get_correlation_score(c.make_variables(records[2], data_point)))
scores.append({
'source':
'Family Profile',
'field':
'Total Members',
'data': [{
'category':
'Weight for Age - Underweight and Severely Underweight',
'score': wfa_score,
'remark': get_correlation_remark(wfa_score),
'variables': c.make_variables(records[0], data_point)
}, {
'category': 'Height for Age - Stunted and Severely Stunted',
'score': hfa_score,
'remark': get_correlation_remark(hfa_score),
'variables': c.make_variables(records[1], data_point)
}, {
'category':
'Weight for Height/Length - Wasted and Severely Wasted',
'score': wfhl_score,
'remark': get_correlation_remark(wfhl_score),
'variables': c.make_variables(records[2], data_point)
}]
})
# educational attainment
for field in datapoints.educational_attainment_for_r:
data_point = socioeconomic.get_educational_attainment(field)
wfa_score = float(
c.get_correlation_score(c.make_variables(records[0], data_point)))
hfa_score = float(
c.get_correlation_score(c.make_variables(records[1], data_point)))
wfhl_score = float(
c.get_correlation_score(c.make_variables(records[2], data_point)))
scores.append({
'source':
'Family Profile',
'field':
field,
'data': [{
'category':
'Weight for Age - Underweight and Severely Underweight',
'score': wfa_score,
'remark': get_correlation_remark(wfa_score),
'variables': c.make_variables(records[0], data_point)
}, {
'category': 'Height for Age - Stunted and Severely Stunted',
'score': hfa_score,
'remark': get_correlation_remark(hfa_score),
'variables': c.make_variables(records[1], data_point)
}, {
'category':
'Weight for Height/Length - Wasted and Severely Wasted',
'score': wfhl_score,
'remark': get_correlation_remark(wfhl_score),
'variables': c.make_variables(records[2], data_point)
}]
})
# water source
for field in datapoints.water_sources:
data_point = socioeconomic.get_water_source(field)
wfa_score = float(
c.get_correlation_score(c.make_variables(records[0], data_point)))
hfa_score = float(
c.get_correlation_score(c.make_variables(records[1], data_point)))
wfhl_score = float(
c.get_correlation_score(c.make_variables(records[2], data_point)))
scores.append({
'source':
'Family Profile',
'field':
field,
'data': [{
'category':
'Weight for Age - Underweight and Severely Underweight',
'score': wfa_score,
'remark': get_correlation_remark(wfa_score),
'variables': c.make_variables(records[0], data_point)
}, {
'category': 'Height for Age - Stunted and Severely Stunted',
'score': hfa_score,
'remark': get_correlation_remark(hfa_score),
'variables': c.make_variables(records[1], data_point)
}, {
'category':
'Weight for Height/Length - Wasted and Severely Wasted',
'score': wfhl_score,
'remark': get_correlation_remark(wfhl_score),
'variables': c.make_variables(records[2], data_point)
}]
})
# toilet type
for field in datapoints.toilet_type:
data_point = socioeconomic.get_toilet_type(field)
wfa_score = float(
c.get_correlation_score(c.make_variables(records[0], data_point)))
hfa_score = float(
c.get_correlation_score(c.make_variables(records[1], data_point)))
wfhl_score = float(
c.get_correlation_score(c.make_variables(records[2], data_point)))
scores.append({
'source':
'Family Profile',
'field':
field,
'data': [{
'category':
'Weight for Age - Underweight and Severely Underweight',
'score': wfa_score,
'remark': get_correlation_remark(wfa_score),
'variables': c.make_variables(records[0], data_point)
}, {
'category': 'Height for Age - Stunted and Severely Stunted',
'score': hfa_score,
'remark': get_correlation_remark(hfa_score),
'variables': c.make_variables(records[1], data_point)
}, {
'category':
'Weight for Height/Length - Wasted and Severely Wasted',
'score': wfhl_score,
'remark': get_correlation_remark(wfhl_score),
'variables': c.make_variables(records[2], data_point)
}]
})
# food production
for field in datapoints.food_production:
data_point = socioeconomic.get_food_production(field)
wfa_score = float(
c.get_correlation_score(c.make_variables(records[0], data_point)))
hfa_score = float(
c.get_correlation_score(c.make_variables(records[1], data_point)))
wfhl_score = float(
c.get_correlation_score(c.make_variables(records[2], data_point)))
scores.append({
'source':
'Family Profile',
'field':
field,
'data': [{
'category':
'Weight for Age - Underweight and Severely Underweight',
'score': wfa_score,
'remark': get_correlation_remark(wfa_score),
'variables': c.make_variables(records[0], data_point)
}, {
'category': 'Height for Age - Stunted and Severely Stunted',
'score': hfa_score,
'remark': get_correlation_remark(hfa_score),
'variables': c.make_variables(records[1], data_point)
}, {
'category':
'Weight for Height/Length - Wasted and Severely Wasted',
'score': wfhl_score,
'remark': get_correlation_remark(wfhl_score),
'variables': c.make_variables(records[2], data_point)
}]
})
return scores
def get_child_care_revised():
scores = []
fields = [
f for f in ChildCare._meta.get_fields()
if f.verbose_name in datapoints.child_care
]
immunization_fields = [
f for f in Immunization._meta.get_fields()
if f.verbose_name in datapoints.immunizations
]
malaria_fields = [
f for f in Malaria._meta.get_fields()
if f.verbose_name in datapoints.malaria
]
tb_fields = [
f for f in Tuberculosis._meta.get_fields()
if f.verbose_name in datapoints.tuberculosis
]
for field in fields:
point = str(field).strip().split(".")[2]
data_point = child_care.get_fhsis(ChildCare, point, None)
wfa_score = float(
c.get_correlation_score(c.make_variables(records[0], data_point)))
hfa_score = float(
c.get_correlation_score(c.make_variables(records[1], data_point)))
wfhl_score = float(
c.get_correlation_score(c.make_variables(records[2], data_point)))
scores.append({
'source':
'Child Care',
'field':
field.verbose_name,
'data': [{
'category':
'Weight for Age - Underweight and Severely Underweight',
'score': wfa_score,
'remark': get_correlation_remark(wfa_score),
'variables': c.make_variables(records[0], data_point)
}, {
'category': 'Height for Age - Stunted and Severely Stunted',
'score': hfa_score,
'remark': get_correlation_remark(hfa_score),
'variables': c.make_variables(records[1], data_point)
}, {
'category':
'Weight for Height/Length - Wasted and Severely Wasted',
'score': wfhl_score,
'remark': get_correlation_remark(wfhl_score),
'variables': c.make_variables(records[2], data_point)
}]
})
for field in immunization_fields:
point = str(field).strip().split(".")[2]
data_point = child_care.get_fhsis(Immunization, point, None)
wfa_score = float(
c.get_correlation_score(c.make_variables(records[0], data_point)))
hfa_score = float(
c.get_correlation_score(c.make_variables(records[1], data_point)))
wfhl_score = float(
c.get_correlation_score(c.make_variables(records[2], data_point)))
scores.append({
'source':
'Immunization',
'field':
field.verbose_name,
'data': [{
'category':
'Weight for Age - Underweight and Severely Underweight',
'score': wfa_score,
'remark': get_correlation_remark(wfa_score),
'variables': c.make_variables(records[0], data_point)
}, {
'category': 'Height for Age - Stunted and Severely Stunted',
'score': hfa_score,
'remark': get_correlation_remark(hfa_score),
'variables': c.make_variables(records[1], data_point)
}, {
'category':
'Weight for Height/Length - Wasted and Severely Wasted',
'score': wfhl_score,
'remark': get_correlation_remark(wfhl_score),
'variables': c.make_variables(records[2], data_point)
}]
})
for field in malaria_fields:
point = str(field).strip().split(".")[2]
data_point = child_care.get_fhsis(Malaria, point, None)
wfa_score = float(
c.get_correlation_score(c.make_variables(records[0], data_point)))
hfa_score = float(
c.get_correlation_score(c.make_variables(records[1], data_point)))
wfhl_score = float(
c.get_correlation_score(c.make_variables(records[2], data_point)))
scores.append({
'source':
'Malaria',
'field':
field.verbose_name,
'data': [{
'category':
'Weight for Age - Underweight and Severely Underweight',
'score': wfa_score,
'remark': get_correlation_remark(wfa_score),
'variables': c.make_variables(records[0], data_point)
}, {
'category': 'Height for Age - Stunted and Severely Stunted',
'score': hfa_score,
'remark': get_correlation_remark(hfa_score),
'variables': c.make_variables(records[1], data_point)
}, {
'category':
'Weight for Height/Length - Wasted and Severely Wasted',
'score': wfhl_score,
'remark': get_correlation_remark(wfhl_score),
'variables': c.make_variables(records[2], data_point)
}]
})
for field in tb_fields:
point = str(field).strip().split(".")[2]
data_point = child_care.get_fhsis(Tuberculosis, point, None)
wfa_score = float(
c.get_correlation_score(c.make_variables(records[0], data_point)))
hfa_score = float(
c.get_correlation_score(c.make_variables(records[1], data_point)))
wfhl_score = float(
c.get_correlation_score(c.make_variables(records[2], data_point)))
scores.append({
'source':
'Tuberculosis',
'field':
field.verbose_name,
'data': [{
'category':
'Weight for Age - Underweight and Severely Underweight',
'score': wfa_score,
'remark': get_correlation_remark(wfa_score),
'variables': c.make_variables(records[0], data_point)
}, {
'category': 'Height for Age - Stunted and Severely Stunted',
'score': hfa_score,
'remark': get_correlation_remark(hfa_score),
'variables': c.make_variables(records[1], data_point)
}, {
'category':
'Weight for Height/Length - Wasted and Severely Wasted',
'score': wfhl_score,
'remark': get_correlation_remark(wfhl_score),
'variables': c.make_variables(records[2], data_point)
}]
})
return scores
