def puntos_equipo(self, indicador=None):
qs_departamento = Departamento.objects.filter(
colaboradores__puntuaciones__rubrica__semana__competencia=self)
filtros = {}
if indicador:
filtros[
'colaboradores__puntuaciones__rubrica__indicador'] = indicador
qs_departamento = qs_departamento.annotate(
puntos=models.Avg('colaboradores__puntuaciones__porcentaje',
output_field=models.DecimalField(
max_digits=5, decimal_places=2),
filter=models.Q(**filtros)))
else:
qs_departamento = qs_departamento.annotate(
puntos=models.Avg('colaboradores__puntuaciones__porcentaje',
output_field=models.DecimalField(
max_digits=5, decimal_places=2)))
return qs_departamento
def get_star_rating(self):
"""
Updates and returns the current avg star rating for an item.
"""
rvws = self.reviews.all()
if rvws.exists():
self.rating = rvws.aggregate(models.Avg('rating'))['rating__avg']
self.save()
return self.rating
return 0
def delete(self, *args, **kwargs):
super().delete(*args, **kwargs)
# Update number of raters and rate average in book when user rate a book
self.book.raters = self.book.user_ratings.count()
self.book.avg_ratings = floor(
self.book.user_ratings.aggregate(models.Avg("rate")).get(
"rate__avg"
)
)
self.book.save()
def get_ratio(self):
"""Obtener el ratio del recurso.
Returns:
float: Ratio medio del recurso.
"""
ratio = self.ratio_resource.aggregate(models.Avg('score'))
if ratio['score__avg']:
return ratio['score__avg']
return 0
def aggregated_user_data(cls, user_id):
record_set = consumption_data.objects.filter(
user_id=user_id).values('user_id')
record_set = record_set.annotate(sum=models.Sum('consumption'),
avg=models.Avg('consumption'))
record_set = dict(user_id=record_set[0]['user_id'],
avg=round(record_set[0]['avg'], 2),
sum=round(record_set[0]['sum'], 2))
return record_set
def get_mma(self):
if not hasattr(self, '_mma'):
mma_anteriores = Dado.objects.filter(acao=self.acao, data__lte=self.data)
if mma_anteriores.count() >= MMA_INTERVAL:
media_vf = mma_anteriores.order_by('-data')[:MMA_INTERVAL].aggregate(models.Avg('valor_fechamento'))
self._mma = media_vf.get('valor_fechamento__avg')
else:
self._mma = None
return self._mma
def adjust_default_row(cls):
defaults = cls.get_default_intervals()
for field in cls._meta.get_fields():
if not re.match(r'[0-9]+\_[0-9]+', field.name):
continue
avg = list(cls.objects.all().aggregate(models.Avg(
field.name)).values())[0]
setattr(defaults, field.name, avg)
defaults.save()
def rating_values(self, character_id):
result = CharacterRating.objects.filter(
character_id=character_id).aggregate(
max_rating=models.Max('rating'),
avg_rating=models.Avg('rating'))
avg_rating = result['avg_rating'] if result['avg_rating'] else 0
return {
'max_rating': result['max_rating'],
'average_rating': round(avg_rating, 1)
}
def update_score(self):
score_owner_object = self.get_score_owner_object()
avg_score = score_owner_object.criterion_scores.filter(
criterion__category_id=self.criterion_category_id).aggregate(
models.Avg('score'))
avg_score = avg_score.get('score__avg')
if avg_score is not None:
self.score = round(avg_score, 2)
self.save(update_fields=['score'])
else:
self.delete()
def save(self, *args, **kwargs):
created = True if not self.id else False
super().save(*args, **kwargs)
if created:
# Update number of raters in book when user rate a book
self.book.raters = self.book.user_ratings.count()
self.book.avg_ratings = floor(
self.book.user_ratings.aggregate(models.Avg("rate")).get(
"rate__avg"
)
)
self.book.save()
def avg_rating(self):
dict = {}
ratings = ChapterRating.objects.filter(chapter__work=self)
avg_rating = ratings.aggregate(models.Avg('score'))['score__avg']
if avg_rating:
dict['rating'] = round(avg_rating / 2.0, 1)
dict['count'] = ratings.count()
else:
dict['rating'] = 0.0
dict['count'] = 0
return dict
def _extra(self, extra_clause, extra_name='datetime'):
query_set = self.extra({
extra_name: extra_clause
}).values(extra_name).annotate(
average_pot=models.Avg('average_pot'),
players_per_flop=models.Avg('players_per_flop'),
unique_player_count=models.Avg('unique_player_count'),
entry_count=models.Avg('entry_count'),
one_tabler_count=models.Avg('one_tabler_count'),
two_tabler_count=models.Avg('two_tabler_count'),
three_tabler_count=models.Avg('three_tabler_count'),
four_tabler_count=models.Avg('four_tabler_count'),
)
return query_set
