def get(self, request, format=None):
if self.request.user is None or self.request.user.id is None or (not User.objects.filter(id=self.request.user.id).exists()):
return Response("Please login first", status=status.HTTP_400_BAD_REQUEST)
user = User.objects.get(id=self.request.user.id)
partner = user.pair.first().get_partner(user) if user.pair.exists() else None
partner_username = request.query_params.get('partner')
if partner_username and (User.objects.filter(username=partner_username).exists()):
partner = User.objects.filter(username=partner_username).first()
if partner.experiment.first() != user.experiment.first():
return Response("The specified partner does not belong to this experiment",
status=status.HTTP_400_BAD_REQUEST)
dictionary = user.experiment.first().dictionary if user.experiment.exists()\
else user.pair.first().assignment.experiment.dictionary
feature_sources = request.query_params.get('feature_source', "system user partner").split(" ")
feature_num = int(request.query_params.get('feature_num', 30))
source_map = {
"system": "system",
"user": user,
"partner": partner,
partner: "partner",
user: "******",
None: "system"
}
source_list = []
for feature_source in feature_sources:
source_list.append(source_map[feature_source])
try:
all_distributions = [];
for source in source_list:
features = dictionary.get_feature_list([source])
distributions = []
distribution_map = {}
for feature in features:
source = feature.source if hasattr(feature, 'source') else "system"
item = {
"feature_id": feature.id,
"feature_index": feature.index,
"feature_text": feature.text,
"source": source_map[source],
"distribution": {},
"normalized_distribution": {},
"total_count": 0,
"entropy": None
}
if feature.origin:
item["origin_message_id"] = feature.origin.id
code = feature.get_origin_message_code()
if code:
item["origin_code_id"] = code.id
item = AttributeDict(item)
for code in corpus_models.Code.objects.all():
item["distribution"][code.text] = 0
distributions.append(item)
distribution_map[feature.index] = item
counts = features.filter(messages__code_assignments__isnull=False,
messages__code_assignments__source=user,
messages__code_assignments__is_user_labeled=True,
messages__code_assignments__valid=True)\
.values('index', 'text', 'messages__code_assignments__code__id', 'messages__code_assignments__code__text')\
.annotate(count=Count('messages')).order_by('id', 'count').all()
for count in counts:
count = AttributeDict(count)
distribution_map[count.index]["distribution"][count.messages__code_assignments__code__text] = count.count
for item in distributions:
item["total_count"] = 0
for code in item.distribution:
item["total_count"] += item.distribution[code]
for code in item.distribution:
if item["total_count"] > 0:
item.normalized_distribution[code] = float(item.distribution[code]) / float(item["total_count"])
else:
item.normalized_distribution[code] = 0
item["entropy"] = entropy(item.distribution)
# first sort by total count
distributions.sort(key=attrgetter("total_count"), reverse=True)
# Then sort by entropy. The order will be equivalent to (entropy, -total_count)
distributions.sort(key=attrgetter("entropy"))
all_distributions = all_distributions + distributions[:feature_num]
output = serializers.FeatureCodeDistributionSerializer(all_distributions, many=True)
return Response(output.data, status=status.HTTP_200_OK)
except:
import traceback
traceback.print_exc()
import pdb
pdb.set_trace()
return Response(status=status.HTTP_400_BAD_REQUEST)
def post(self, request, format=None):
if self.request.user is None or self.request.user.id is None or (not User.objects.filter(id=self.request.user.id).exists()):
return Response("Please login first", status=status.HTTP_400_BAD_REQUEST)
user = User.objects.get(id=self.request.user.id)
dictionary = user.experiment.first().dictionary if user.experiment.exists()\
else user.pair.first().assignment.experiment.dictionary
input = serializers.FeatureSerializer(data=request.data)
if input.is_valid():
data = input.validated_data
token_list = data["token_list"]
origin = data["origin"]
feature = dictionary.add_feature(token_list, source=user, origin=origin)
item = {
"feature_id": feature.id,
"feature_index": feature.index,
"feature_text": feature.text,
"source": "user",
"distribution": {},
"normalized_distribution": {},
"total_count": 0,
"entropy": None
}
if feature.origin:
item["origin_message_id"] = feature.origin.id
code = feature.get_origin_message_code()
if code:
item["origin_code_id"] = code.id
item = AttributeDict(item)
for code in corpus_models.Code.objects.all():
item["distribution"][code.text] = 0
counts = enhance_models.Feature.objects\
.filter(id=feature.id, messages__code_assignments__isnull=False,
messages__code_assignments__is_user_labeled=True,
messages__code_assignments__source=user,
messages__code_assignments__valid=True)\
.values('index', 'text', 'messages__code_assignments__code__id', 'messages__code_assignments__code__text')\
.annotate(count=Count('messages')).order_by('id', 'count').all()
for count in counts:
count = AttributeDict(count)
item["distribution"][count.messages__code_assignments__code__text] = count.count
item["total_count"] = 0
for code in item.distribution:
item["total_count"] += item.distribution[code]
for code in item.distribution:
if item["total_count"] > 0:
item.normalized_distribution[code] = float(item.distribution[code]) / float(item["total_count"])
else:
item.normalized_distribution[code] = 0
item["entropy"] = entropy(item.distribution)
output = serializers.FeatureCodeDistributionSerializer(item)
return Response(output.data, status=status.HTTP_200_OK)
return Response(input.errors, status=status.HTTP_400_BAD_REQUEST)