study = StudySerializer()
inclusion_criteria = serializers.StringRelatedField(many=True)
exclusion_criteria = serializers.StringRelatedField(many=True)
url = serializers.ReadOnlyField(source="get_absolute_url")
protocol_type = serializers.ReadOnlyField(source="get_protocol_type_display")
lit_search_strategy = serializers.ReadOnlyField(source="get_lit_search_strategy_display")
results = MetaResultLinkSerializer(many=True)
class Meta:
model = models.MetaProtocol
class MetaResultSerializer(serializers.ModelSerializer):
protocol = MetaProtocolSerializer()
url = serializers.ReadOnlyField(source="get_absolute_url")
metric = ResultMetricSerializer()
adjustment_factors = serializers.StringRelatedField(many=True)
single_results = SingleResultSerializer(many=True)
def to_representation(self, instance):
ret = super(MetaResultSerializer, self).to_representation(instance)
ret['estimateFormatted'] = instance.estimate_formatted
return ret
class Meta:
model = models.MetaResult
SerializerHelper.add_serializer(models.MetaProtocol, MetaProtocolSerializer)
SerializerHelper.add_serializer(models.MetaResult, MetaResultSerializer)
can_create_sets = serializers.BooleanField(read_only=True)
effects = EffectTagsSerializer()
diagnostic = serializers.CharField(source='get_diagnostic_display', read_only=True)
url = serializers.CharField(source='get_absolute_url', read_only=True)
results = ResultSerializer(many=True)
comparison_sets = ComparisonSetLinkSerializer(many=True)
class Meta:
model = models.Outcome
class ComparisonSetSerializer(serializers.ModelSerializer):
url = serializers.CharField(source='get_absolute_url', read_only=True)
exposure = ExposureSerializer()
outcome = OutcomeSerializer()
study_population = StudyPopulationSerializer()
groups = GroupSerializer(many=True)
class Meta:
model = models.ComparisonSet
class OutcomeCleanupFieldsSerializer(DynamicFieldsMixin, serializers.ModelSerializer):
class Meta:
model = models.Outcome
cleanup_fields = model.TEXT_CLEANUP_FIELDS
fields = cleanup_fields + ('id', )
SerializerHelper.add_serializer(models.Outcome, OutcomeSerializer)
class FinalRobStudySerializer(StudySerializer):
assessment = serializers.PrimaryKeyRelatedField(read_only=True)
riskofbiases = RiskOfBiasSerializer(many=True, read_only=True)
class Meta:
model = models.Study
exclude = (
'searches',
'identifiers',
)
def to_representation(self, instance):
instance.riskofbiases = instance.riskofbiases.filter(final=True)
ret = super().to_representation(instance)
return ret
class StudyCleanupFieldsSerializer(DynamicFieldsMixin,
serializers.ModelSerializer):
class Meta:
model = models.Study
cleanup_fields = model.TEXT_CLEANUP_FIELDS
fields = (
'id',
'short_citation',
) + cleanup_fields
SerializerHelper.add_serializer(models.Study, VerboseStudySerializer)
protocol_type = serializers.ReadOnlyField(
source="get_protocol_type_display")
lit_search_strategy = serializers.ReadOnlyField(
source="get_lit_search_strategy_display")
results = MetaResultLinkSerializer(many=True)
class Meta:
model = models.MetaProtocol
fields = '__all__'
class MetaResultSerializer(serializers.ModelSerializer):
protocol = MetaProtocolSerializer()
url = serializers.ReadOnlyField(source="get_absolute_url")
metric = ResultMetricSerializer()
adjustment_factors = serializers.StringRelatedField(many=True)
single_results = SingleResultSerializer(many=True)
def to_representation(self, instance):
ret = super().to_representation(instance)
ret['estimateFormatted'] = instance.estimate_formatted
return ret
class Meta:
model = models.MetaResult
fields = '__all__'
SerializerHelper.add_serializer(models.MetaProtocol, MetaProtocolSerializer)
SerializerHelper.add_serializer(models.MetaResult, MetaResultSerializer)
study = StudyAssessmentSerializer(read_only=True)
type_display = serializers.CharField(source='get_type_display')
status_display = serializers.CharField(source='get_status_display')
class Meta:
model = models.Task
fields = '__all__'
read_only_fields = (
'id',
'study',
'open',
'started',
'completed',
)
def update(self, instance, validated_data):
if self.initial_data['owner']:
owner_id = self.initial_data['owner']['id']
instance.owner = HAWCUser.objects.get(pk=owner_id)
instance.save()
return super().update(instance, validated_data)
class TaskByAssessmentSerializer(TaskSerializer):
study = StudyAssessmentSerializer(read_only=True)
class Meta(TaskSerializer.Meta):
depth = 2
SerializerHelper.add_serializer(models.Task, TaskSerializer)
ret["settings"] = settings
return ret
class Meta:
model = models.Visual
exclude = ('endpoints', )
class VisualSerializer(CollectionVisualSerializer):
def to_representation(self, instance):
ret = super().to_representation(instance)
ret['url_update'] = instance.get_update_url()
ret['url_delete'] = instance.get_delete_url()
ret["endpoints"] = [
SerializerHelper.get_serialized(d, json=False)
for d in instance.get_endpoints()
]
ret["studies"] = [
SerializerHelper.get_serialized(d, json=False)
for d in instance.get_studies()
]
return ret
SerializerHelper.add_serializer(models.Visual, VisualSerializer)
class Meta:
model = models.StudyQuality
exclude = ('object_id', 'content_type')
class StudySerializer(serializers.ModelSerializer):
def to_representation(self, instance):
ret = super(StudySerializer, self).to_representation(instance)
ret['study_type'] = instance.get_study_type_display()
ret['coi_reported'] = instance.get_coi_reported_display()
ret['url'] = instance.get_absolute_url()
return ret
class Meta:
model = models.Study
class VerboseStudySerializer(StudySerializer):
assessment = serializers.PrimaryKeyRelatedField(read_only=True)
searches = serializers.PrimaryKeyRelatedField(many=True, read_only=True)
qualities = StudyQualitySerializer(many=True, read_only=True)
identifiers = IdentifiersSerializer(many=True)
tags = ReferenceTagsSerializer()
class Meta:
model = models.Study
SerializerHelper.add_serializer(models.Study, VerboseStudySerializer)
class Meta:
model = models.RiskOfBiasScore
fields = ('id', 'score', 'notes', 'metric')
class RiskOfBiasSerializer(serializers.ModelSerializer):
scores = RiskOfBiasScoreSerializer(read_only=False, many=True, partial=True)
author = HAWCUserSerializer(read_only=True)
class Meta:
model = models.RiskOfBias
fields = ('id', 'author', 'active',
'final', 'study', 'created',
'last_updated', 'scores')
def update(self, instance, validated_data):
"""
Updates the nested RiskOfBiasScores with submitted data before updating
the RiskOfBias instance.
"""
score_data = validated_data.pop('scores')
for score, form_data in zip(instance.scores.all(), score_data):
for field, value in form_data.items():
setattr(score, field, value)
score.save()
return super(RiskOfBiasSerializer, self).update(instance, validated_data)
SerializerHelper.add_serializer(models.RiskOfBias, RiskOfBiasSerializer)
from rest_framework import serializers
from utils.helper import SerializerHelper
from . import models
class HAWCUserSerializer(serializers.ModelSerializer):
full_name = serializers.CharField(source='get_full_name')
class Meta:
model = models.HAWCUser
fields = (
'id',
'full_name',
)
SerializerHelper.add_serializer(models.HAWCUser, HAWCUserSerializer)
models.EndpointGroup.percentControl(ret['data_type'], ret['endpoint_group'])
# get individual animal data
if instance.individual_animal_data:
models.EndpointGroup.getIndividuals(instance, ret['endpoint_group'])
# get BMD
ret['BMD'] = None
try:
model = instance.BMD_session.latest().selected_model
if model is not None:
ret['BMD'] = BMDModelRunSerializer().to_representation(model)
except instance.BMD_session.model.DoesNotExist:
pass
return ret
class Meta:
model = models.Endpoint
class AggregationSerializer(serializers.ModelSerializer):
endpoints = EndpointSerializer(many=True)
class Meta:
model = models.Aggregation
SerializerHelper.add_serializer(models.Endpoint, EndpointSerializer)
SerializerHelper.add_serializer(models.Aggregation, AggregationSerializer)
url = serializers.CharField(source='get_absolute_url', read_only=True)
results = ResultSerializer(many=True)
comparison_sets = ComparisonSetLinkSerializer(many=True)
class Meta:
model = models.Outcome
fields = '__all__'
class ComparisonSetSerializer(serializers.ModelSerializer):
url = serializers.CharField(source='get_absolute_url', read_only=True)
exposure = ExposureSerializer()
outcome = OutcomeSerializer()
study_population = StudyPopulationSerializer()
groups = GroupSerializer(many=True)
class Meta:
model = models.ComparisonSet
fields = '__all__'
class OutcomeCleanupFieldsSerializer(DynamicFieldsMixin,
serializers.ModelSerializer):
class Meta:
model = models.Outcome
cleanup_fields = model.TEXT_CLEANUP_FIELDS
fields = cleanup_fields + ('id', )
SerializerHelper.add_serializer(models.Outcome, OutcomeSerializer)
from rest_framework import serializers
from utils.helper import SerializerHelper
from . import models
class HAWCUserSerializer(serializers.ModelSerializer):
full_name = serializers.CharField(source='get_full_name')
class Meta:
model = models.HAWCUser
fields = ('id', 'full_name', )
SerializerHelper.add_serializer(models.HAWCUser, HAWCUserSerializer)
settings = {}
ret["settings"] = settings
return ret
class Meta:
model = models.Visual
exclude = ('endpoints', )
class VisualSerializer(CollectionVisualSerializer):
def to_representation(self, instance):
ret = super().to_representation(instance)
ret['url_update'] = instance.get_update_url()
ret['url_delete'] = instance.get_delete_url()
ret["endpoints"] = [
SerializerHelper.get_serialized(d, json=False)
for d in instance.get_endpoints()
]
ret["studies"] = [
SerializerHelper.get_serialized(d, json=False)
for d in instance.get_studies()
]
return ret
SerializerHelper.add_serializer(models.Visual, VisualSerializer)
endpoints = MiniIVEndpointSerializer(many=True)
class IVEndpointCleanupFieldsSerializer(DynamicFieldsMixin,
serializers.ModelSerializer):
study_short_citation = serializers.SerializerMethodField()
class Meta:
model = models.IVEndpoint
cleanup_fields = ('study_short_citation', ) + model.TEXT_CLEANUP_FIELDS
fields = cleanup_fields + ('id', )
def get_study_short_citation(self, obj):
return obj.experiment.study.short_citation
class IVChemicalCleanupFieldsSerializer(DynamicFieldsMixin,
serializers.ModelSerializer):
study_short_citation = serializers.SerializerMethodField()
class Meta:
model = models.IVChemical
cleanup_fields = ('study_short_citation', ) + model.TEXT_CLEANUP_FIELDS
fields = cleanup_fields + ('id', )
def get_study_short_citation(self, obj):
return obj.study.short_citation
SerializerHelper.add_serializer(models.IVEndpoint, IVEndpointSerializer)
ret = super(MetaProtocolSerializer, self).to_representation(instance)
ret['url'] = instance.get_absolute_url()
ret['protocol_type'] = instance.get_protocol_type_display()
ret['lit_search_strategy'] = instance.get_lit_search_strategy_display()
return ret
class Meta:
model = models.MetaProtocol
class MetaResultSerializer(serializers.ModelSerializer):
protocol = MetaProtocolSerializer()
statistical_metric = StatisticalMetricSerializer()
single_results = SingleResultSerializer(many=True)
adjustment_factors = serializers.StringRelatedField(many=True)
def to_representation(self, instance):
ret = super(MetaResultSerializer, self).to_representation(instance)
ret['url'] = instance.get_absolute_url()
ret['estimateFormatted'] = instance.estimate_formatted
return ret
class Meta:
model = models.MetaResult
SerializerHelper.add_serializer(models.StudyPopulation, StudyPopulationSerializer)
SerializerHelper.add_serializer(models.AssessedOutcome, AssessedOutcomeSerializer)
SerializerHelper.add_serializer(models.MetaProtocol, MetaProtocolSerializer)
SerializerHelper.add_serializer(models.MetaResult, MetaResultSerializer)
experiment = serializers.PrimaryKeyRelatedField(read_only=True)
chemical = _IVChemicalSerializer()
groups = serializers.PrimaryKeyRelatedField(read_only=True, many=True)
benchmarks = serializers.PrimaryKeyRelatedField(read_only=True, many=True)
category = serializers.PrimaryKeyRelatedField(read_only=True)
def to_representation(self, instance):
ret = super(MiniIVEndpointSerializer, self).to_representation(instance)
ret['url'] = instance.get_absolute_url()
return ret
class Meta:
model = models.IVEndpoint
class IVExperimentSerializerFull(IVExperimentSerializer):
url_update = serializers.CharField(source='get_update_url', read_only=True)
url_delete = serializers.CharField(source='get_delete_url', read_only=True)
url_create_endpoint = serializers.CharField(source='get_endpoint_create_url', read_only=True)
endpoints = MiniIVEndpointSerializer(many=True)
class CleanupFieldsSerializer(DynamicFieldsMixin, serializers.ModelSerializer):
class Meta:
model = models.IVEndpoint
cleanup_fields = model.text_cleanup_fields()
fields = cleanup_fields + ('id', 'name')
SerializerHelper.add_serializer(models.IVEndpoint, IVEndpointSerializer)
"""
score_data = validated_data.pop('scores')
for score, form_data in zip(instance.scores.all(), score_data):
for field, value in list(form_data.items()):
setattr(score, field, value)
score.save()
return super().update(instance, validated_data)
class AssessmentMetricScoreSerializer(serializers.ModelSerializer):
scores = serializers.SerializerMethodField('get_final_score')
class Meta:
model = models.RiskOfBiasMetric
fields = ('id', 'name', 'description', 'scores')
def get_final_score(self, instance):
scores = instance.scores.filter(riskofbias__final=True,
riskofbias__active=True)
serializer = RiskOfBiasScoreSerializer(scores, many=True)
return serializer.data
class AssessmentRiskOfBiasScoreSerializer(serializers.ModelSerializer):
class Meta:
model = models.RiskOfBiasScore
fields = ('id', 'notes', 'score')
SerializerHelper.add_serializer(models.RiskOfBias, RiskOfBiasSerializer)