def test_add_normalized_rating(self):
"""Checks that the user average is substracted from all the ratings."""
ratings = self.get_ratings()
Builder.add_normalized_rating(ratings)
norm_ratings = ratings[ratings['userid'] == 3]
self.assertAlmostEqual(norm_ratings.iloc[0]['movieid'], 0)
self.assertAlmostEqual(norm_ratings.iloc[0]['normalized_rating'], 0.4)
self.assertAlmostEqual(norm_ratings.iloc[1]['movieid'], 2)
self.assertAlmostEqual(norm_ratings.iloc[1]['normalized_rating'], 0.4)
self.assertAlmostEqual(norm_ratings.iloc[2]['movieid'], 3)
self.assertAlmostEqual(norm_ratings.iloc[2]['normalized_rating'], 2.4)
self.assertAlmostEqual(norm_ratings.iloc[3]['movieid'], 4)
self.assertAlmostEqual(norm_ratings.iloc[3]['normalized_rating'], -1.6)
self.assertAlmostEqual(norm_ratings.iloc[4]['movieid'], 5)
self.assertAlmostEqual(norm_ratings.iloc[4]['normalized_rating'], -1.6)
def test_build_similarity_model(self):
"""Checks that the similarity model is calculated correct."""
ratings = self.get_ratings()
model = Builder.build_similarity_model(ratings)
self.assertIsNotNone(model)
self.assertEqual(len(model), 15)
# item 0 and 2 has identical ratings. Their similarity should therefore be 1.0
self.assertAlmostEqual(model[frozenset({0, 2})], 1.0)
def user_evidence(request, userid):
cursor = connection.cursor()
cursor.execute('SELECT \
user_id, \
content_id,\
mov.title,\
count(case when event = \'buy\' then 1 end) as buys,\
count(case when event = \'details\' then 1 end) as details,\
count(case when event = \'moredetails\' then 1 end) as moredetails\
FROM \
public."evidenceCollector_log" log\
JOIN public.movies mov \
ON CAST(log.content_id AS VARCHAR(50)) = CAST(mov.id AS VARCHAR(50))\
WHERE\
user_id = \'%s\'\
group by log.user_id, log.content_id, mov.title\
order by log.user_id, log.content_id' % userid)
data = dictfetchall(cursor)
movie_ratings = Builder.generate_implicit_ratings(data)
Builder.save_ratings(userid, movie_ratings)
return JsonResponse(movie_ratings, safe=False)
def user_evidence(request, userid):
cursor = connection.cursor()
cursor.execute('SELECT \
user_id, \
content_id,\
mov.title,\
count(case when event = \'buy\' then 1 end) as buys,\
count(case when event = \'details\' then 1 end) as details,\
count(case when event = \'moredetails\' then 1 end) as moredetails\
FROM \
public."evidenceCollector_log" log\
JOIN public.movies mov \
ON CAST(log.content_id AS VARCHAR(50)) = CAST(mov.id AS VARCHAR(50))\
WHERE\
user_id = \'%s\'\
group by log.user_id, log.content_id, mov.title\
order by log.user_id, log.content_id' % userid)
data = dictfetchall(cursor)
movie_ratings = Builder.generate_implicit_ratings(data)
Builder.save_ratings(userid, movie_ratings)
return JsonResponse(movie_ratings, safe=False)
def build_similarity_model(request):
Builder.build_item_collaborative_model()
def build_similarity_model(request):
Builder.build_item_collaborative_model()
