def driver():
'''
Testing recommender assignment functions with Duke eateries
'''
(items, ratings) = SmallDukeEatsReader.getdata()
# print("items = ",items)
# print("ratings = ", ratings)
avg = RecommenderEngine.averages(items, ratings)
# print("average",avg)
if avg == correctAvg:
print('averages works')
else:
print('average fails')
for key in ratings:
slist = RecommenderEngine.similarities(key, ratings)
# print(key,slist)
r3 = RecommenderEngine.recommendations(key, items, ratings, 3)
# print("top",r3)
if key == 'Sung-Hoon' and slist == correctSim:
print('similarities works')
elif key == 'Sung-Hoon' and slist != correctSim:
print('similarities fails')
if key == 'Sarah Lee' and r3 == correctRec:
print('recommendations works')
elif key == 'Sarah Lee' and r3 != correctRec:
print('recommendations fails')
def driver():
(items,ratings) = SmallDukeEatsReader.getdata()
print("items = ",items)
print("ratings = ", ratings)
avg = RecommenderEngine.averages(items,ratings)
if avg == [('DivinityCafe', 4.0), ('TheCommons', 3.0), ('Tandoor', 2.4285714285714284), ('IlForno', 1.8),
('FarmStead', 1.4), ('LoopPizzaGrill', 1.0), ('TheSkillet', 0.0), ('PandaExpress', -0.2),
('McDonalds', -0.3333333333333333)]:
print("averages work")
else:
print("averages fails")
similarities = RecommenderEngine.similarities("Sung-Hoon", ratings)
if similarities == [('Wei', 1), ('Sly one', -1), ('Melanie', -2), ('Sarah Lee', -6), ('J J', -14), ('Harry', -24),
('Nana Grace', -29)]:
print("similarities work")
else:
print("similarities fails")
recommendations = RecommenderEngine.recommendations("Sarah Lee", ["DivinityCafe", "FarmStead", "IlForno","LoopPizzaGrill", "McDonalds", "PandaExpress",
"Tandoor", "TheCommons", "TheSkillet"], {"Sarah Lee":[3, 3, 3, 3, 0, -3, 5, 0, -3], "Melanie":
[5, 0, 3, 0, 1, 3, 3, 3, 1],"J J":[0, 1, 0, -1, 1, 1, 3, 0, 1], "Sly one":[5, 0, 1, 3, 0, 0, 3, 3, 3],
"Sung-Hoon": [0, -1, -1, 5, 1, 3, -3, 1, -3], "Nana Grace":[5, 0, 3, -5, -1, 0, 1, 3, 0], "Harry":
[5, 3, 0, -1, -3, -5, 0, 5, 1], "Wei":[1, 1, 0, 3, -1, 0, 5, 3, 0]}, 3)
if recommendations == [('Tandoor', 149.5), ('TheCommons', 128.0), ('DivinityCafe', 123.33333333333333), ('FarmStead', 69.5),
('TheSkillet', 66.0), ('LoopPizzaGrill', 62.0), ('IlForno', 33.0), ('McDonalds', -69.5), ('PandaExpress', -165.0)]:
print("recommendations work")
else:
print("recommendations fails")
def driver():
'''(items,ratings) = SmallDukeEatsReader.getdata()
print("items = ",items)
print("ratings = ", ratings)'''
avg = RecommenderEngine.averages(items, ratings)
print("average", avg)
slist = RecommenderEngine.similarities("student1", ratings)
print(slist)
for key in ratings:
slist = RecommenderEngine.similarities(key, ratings)
print(key, slist)
r3 = RecommenderEngine.recommendations("student1", items, ratings, 2)
print(r3)
print(MovieReader.getdata()[:5])
print(BookReader.getdata()[:5])
def driver():
(items, ratings) = SmallDukeEatsReader.getdata()
print("items = ", items)
print("ratings = ", ratings)
avg = RecommenderEngine.averages(items, ratings)
print("average", avg)
for key in ratings:
slist = RecommenderEngine.similarities(key, ratings)
print(key, slist)
r3 = RecommenderEngine.recommendations(key, items, ratings, 3)
print("top", r3)
def driver():
'''
This function uses the file SmallDukeEatsReads to test functions
in RecommenderEngine by outputting validation messages.
'''
(items, ratings) = SmallDukeEatsReader.getdata()
print("items = ", items) #len 9
print("ratings = ", ratings)
avg = RecommenderEngine.averages(items, ratings)
print("average", avg)
if avg == [('DivinityCafe', 4.0), ('TheCommons', 3.0),
('Tandoor', 2.4285714285714284), ('IlForno', 1.8),
('FarmStead', 1.4), ('LoopPizzaGrill', 1.0),
('TheSkillet', 0.0), ('PandaExpress', -0.2),
('McDonalds', -0.3333333333333333)]:
print("averages works")
else:
print("averages fails")
for key in ratings:
slist = RecommenderEngine.similarities(key, ratings)
print(key, slist)
if key == "Sung-Hoon":
if slist == [('Wei', 1), ('Sly one', -1), ('Melanie', -2),
('Sarah Lee', -6), ('J J', -14), ('Harry', -24),
('Nana Grace', -29)]:
print("similarities works")
else:
print("similarities fails")
r3 = RecommenderEngine.recommendations(key, items, ratings, 3)
if key == "Sarah Lee":
if r3 == [('Tandoor', 149.5), ('TheCommons', 128.0),
('DivinityCafe', 123.33333333333333),
('FarmStead', 69.5), ('TheSkillet', 66.0),
('LoopPizzaGrill', 62.0), ('IlForno', 33.0),
('McDonalds', -69.5), ('PandaExpress', -165.0)]:
print("recommendations works")
else:
print("recommendations fails")
print("top", r3)
def driver():
(items, ratings) = SmallDukeEatsReader.getdata()
print("items = ", items)
print("ratings = ", ratings)
avg = RecommenderEngine.averages(items, ratings)
print("average", avg)
answer = [('DivinityCafe', 4.0), ('TheCommons', 3.0),
('Tandoor', 2.4285714285714284), ('IlForno', 1.8),
('FarmStead', 1.4), ('LoopPizzaGrill', 1.0), ('TheSkillet', 0.0),
('PandaExpress', -0.2), ('McDonalds', -0.3333333333333333)]
if avg == answer:
print("average works")
else:
print("average fails")
for key in ratings:
slist = RecommenderEngine.similarities(key, ratings)
print(key, slist)
answer = [('Wei', 1), ('Sly one', -1), ('Melanie', -2),
('Sarah Lee', -6), ('J J', -14), ('Harry', -24),
('Nana Grace', -29)]
if answer == slist and key == 'Sung-Hoon':
print("similarities works")
if answer != slist and key == 'Sung-Hoon':
print("similarities fails")
r3 = RecommenderEngine.recommendations(key, items, ratings, 3)
print("top", r3)
answer = [('Tandoor', 149.5), ('TheCommons', 128.0),
('DivinityCafe', 123.33333333333333), ('FarmStead', 69.5),
('TheSkillet', 66.0), ('LoopPizzaGrill', 62.0),
('IlForno', 33.0), ('McDonalds', -69.5),
('PandaExpress', -165.0)]
if answer == r3 and key == 'Sarah Lee':
print("recommendations works")
if answer != r3 and key == 'Sarah Lee':
print("recommendations fails")
def driver():
(items, ratings) = SmallDukeEatsReader.getdata()
print("items = ", items)
print("ratings = ", ratings)
avg = RecommenderEngine.averages(items, ratings)
if avg == [('DivinityCafe', 4.0), ('TheCommons', 3.0),
('Tandoor', 2.4285714285714284), ('IlForno', 1.8),
('FarmStead', 1.4), ('LoopPizzaGrill', 1.0),
('TheSkillet', 0.0), ('PandaExpress', -0.2),
('McDonalds', -0.3333333333333333)]:
print("AVERAGES WORKS")
else:
print("AVERAGES FAILS")
print("average", avg)
for key in ratings:
slist = RecommenderEngine.similarities(key, ratings)
print(key, slist)
r3 = RecommenderEngine.recommendations(key, items, ratings, 3)
print("top", r3)
Created on Nov 24, 2015
@author: ola
'''
import RecommenderEngine, json
import SimpleFoodReader
import BookReader
import MovieReader
if __name__ == "__main__":
#(jitems,jratings) = SimpleFoodReader.getData("foodratings_example.txt")
(jitems, jratings) = BookReader.getData("bookratings.txt")
#(jitems,jratings) = MovieReader.getData("movieratings.txt")
print "items = ", jitems
print "ratings = ", jratings
items = json.loads(jitems)
ratings = json.loads(jratings)
avg = RecommenderEngine.averages(items, ratings)
print avg
for key in ratings:
slist = RecommenderEngine.similarities(key, ratings)
print key, slist
print "\t", RecommenderEngine.scores(slist, items, ratings, 1)
print "\t", RecommenderEngine.scores(slist, items, ratings, len(slist))
print RecommenderEngine.recommend(ratings.keys()[0], items, ratings, 5)
#for the above test, I randomly chose a name and a count
Created on Nov 24, 2015
@author: ola
'''
import RecommenderEngine, json
import SimpleFoodReader
import BookReader
import MovieReader
if __name__ == "__main__":
#(jitems,jratings) = SimpleFoodReader.getData("foodratings_example.txt")
(jitems,jratings) = BookReader.getData("bookratings.txt")
#(jitems,jratings) = MovieReader.getData("movieratings.txt")
print "items = ",jitems
print "ratings = ", jratings
items = json.loads(jitems)
ratings = json.loads(jratings)
avg = RecommenderEngine.averages(items,ratings)
print avg
for key in ratings:
slist = RecommenderEngine.similarities(key,ratings)
print key,slist
print "\t",RecommenderEngine.scores(slist,items,ratings,1)
print "\t",RecommenderEngine.scores(slist,items,ratings,len(slist))
print RecommenderEngine.recommend(ratings.keys()[0], items, ratings, 5)
#for the above test, I randomly chose a name and a count
for i in ratings:
if i == name:
person = ratings[i]
break
counter = 0
for i in range(0, len(items)):
if counter == top:
break
if person[i] == 0:
tuple = (items[i], newList[i][1])
topThree.append(tuple)
counter += 1
if len(topThree):
for i in range(0, top):
topThree.append(newList[i])
return topThree
if __name__ == '__main__':
name = 'Jeanice'
items = ['lions', 'tigers', 'bears']
ratings = dict([('Nohemi', [1, -2, 1]), ('Ines', [-2, 2, 0]),
('Evelynn', [-1, -2, -1]), ('Jeanice', [1, -2, 1])])
size = 2
sim = RecommenderEngine.similarities(name, ratings)
print('sim =', sim) # Printing for your convenience
ret = RecommenderEngine.recommendations(name, items, ratings, size)
print(ret[0][0])
print(ret[0][1])
def test_similarities(self):
self.assertEqual(RecommenderEngine.similarities("student1", ratings),
[('student2', 5), ('student3', 4)])