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