def dehydrate(self, bundle):
"""inject extra info"""
event, data = bundle.obj, bundle.data
category_resource = self.concrete_category.get_related_resource(bundle.obj.concrete_category)
ctree = CachedCategoryTree()
# concrete parent category
concrete_parent_category = ctree.surface_parent(event.concrete_category_id)
concrete_parent_category_uri = category_resource.get_resource_uri(concrete_parent_category)
data.update(concrete_parent_category=concrete_parent_category_uri)
# concrete breadcrumbs :)
concrete_category_breadcrumb_uris = []
for category in ctree.parents(event.concrete_category_id):
concrete_category_breadcrumb_uris.append(category_resource.get_resource_uri(category))
data.update(concrete_category_breadcrumbs=concrete_category_breadcrumb_uris)
# detail image thumbnail
try:
image = event.image_chain(ctree)
detail_thumb = get_thumbnail(image, **settings.IPHONE_THUMB_OPTIONS)
except Exception:
pass
else:
data.update(thumbnail_detail=detail_thumb.url)
return super(EventResource, self).dehydrate(bundle)
def dehydrate(self, bundle):
"""inject extra info"""
event, data = bundle.obj, bundle.data
category_resource = self.concrete_category.get_related_resource(
bundle.obj.concrete_category)
ctree = CachedCategoryTree()
# concrete parent category
concrete_parent_category = ctree.surface_parent(
event.concrete_category_id)
concrete_parent_category_uri = category_resource.get_resource_uri(
concrete_parent_category)
data.update(concrete_parent_category=concrete_parent_category_uri)
# concrete breadcrumbs :)
concrete_category_breadcrumb_uris = []
for category in ctree.parents(event.concrete_category_id):
concrete_category_breadcrumb_uris.append(
category_resource.get_resource_uri(category))
data.update(
concrete_category_breadcrumbs=concrete_category_breadcrumb_uris)
# detail image thumbnail
try:
image = event.image_chain(ctree)
detail_thumb = get_thumbnail(image,
**settings.IPHONE_THUMB_OPTIONS)
except Exception:
pass
else:
data.update(thumbnail_detail=detail_thumb.url)
return super(EventResource, self).dehydrate(bundle)
def test_convergence(self):
categories = ml.recommend_categories(self.user)
#print "Categories: ", categories
picked_category = ml.sample_distribution(categories.items())[0]
#print "picked category: ", picked_category
picked_aggr = EventActionAggregate(user=self.user, category=picked_category)
lst = []
ctree = CachedCategoryTree()
parents = ctree.parents(picked_category)
count = 0
while count < 100:
count +=1
print "Round: %d\r"%count,
sys.stdout.flush()
# recommend a new set of categories
recommendation_scores = ml.recommend_categories(self.user)
cats = ml.sample_category_distribution(recommendation_scores.items(),
settings.N)
found_count = cats.count(picked_category)
#print "Categories: ",cats
#print "ID: ", picked_category.id
cats = set(cats)
cats.discard(picked_category.id)
# # G(oto) picked category
picked_aggr.g += found_count
picked_aggr.save()
# X all other categories
for c in cats:
if c in parents:
continue
try:
eaa = EventActionAggregate.objects.get(user=self.user, category=c)
except EventActionAggregate.DoesNotExist:
eaa = EventActionAggregate(user=self.user, category=c)
eaa.x += 1
eaa.save()
lst.append(found_count*100.0/settings.N)
plt.plot(lst,color="blue")
plt.title("Rate of learning one category")
plt.xlabel("Trials")
plt.ylabel("% of all Recommendations")
plt.savefig("learning/test_results/test.pdf")
plt.cla()
self.assertTrue(True)
