def tropes_recommend(list_of_movies, nr_of_wanted_recs=10):
logger = logging.getLogger('cutter')
hdlr = logging.FileHandler('log.log')
formatter = logging.Formatter('%(asctime)s %(message)s')
hdlr.setFormatter(formatter)
logger.addHandler(hdlr)
logger.setLevel(logging.WARNING)
movies = movies_to_nrs(sorted([(title, score) for (title, score) in list_of_movies]))
movies_set = set(movie for (movie, _) in movies)
logger.warning('Movies transformed into numbers - ' + str(len(movies)) + ' transformed correctly!')
# print 'Movies transformed into numbers - ' + str(len(movies)) + ' transformed correctly!'
if len(movies) == 0:
return dict()
matrix = ofile("matrix-20140601.lst")
logger.warning('Matrix loaded!')
# print 'Matrix loaded!'
sim_matrix = ofile("similarity.lst")
logger.warning('Similarity matrix loaded!')
# print 'Similarity matrix loaded!'
movie_list = ofile("movies.lst")
weight_sum = sum(float(score) for (_, score) in movies)
recommended = []
for movie in range(len(movie_list)):
if movie not in movies_set:
suma = 0.0
sum_of_sim = 0.0
for rated in movies:
sim = get_similarity(sim_matrix, movie, rated[0], len(movie_list))
sum_of_sim += sim
suma += sim * (float(rated[1]) - 2.5)
if sum_of_sim > 0.0:
suma = (suma / (sum_of_sim))
if suma > -1.0:
recommended.append((suma + 2.5, movie_list[movie]))
# if movie % 100 == 0:
# logger.warning(str(movie) + ' recommendations created!')
# print str(movie) + ' recommendations created!'
recommended = sorted(recommended, key=lambda tup: tup[0], reverse=True)
logger.warning('Recommendations created!')
# print 'Recommendations created!'
if len(recommended) >= nr_of_wanted_recs:
recommended = recommended[:nr_of_wanted_recs]
return dict([(movie_str.split(" @|@ ")[0][1:-1], round(score)) for (score, movie_str) in recommended])
def movies_to_nrs(s_movies):
movies = ofile("movies.lst")
counter = 0
m_counter = 0
ret_list = []
for line in movies:
if s_movies[counter][0][1] < line[1]:
counter += 1
if counter == len(s_movies):
return ret_list
if s_movies[counter][0] == line.split(" @|@ ")[0][1:-1]:
ret_list.append((m_counter, s_movies[counter][1]))
counter += 1
if counter == len(s_movies):
return ret_list
m_counter += 1
return ret_list
logger.addHandler(hdlr)
logger.setLevel(logging.WARNING)
metric = "euclidean"
try:
metric = sys.argv[1]
print metric
except:
logger.warning("Unknown metric given as argument!")
print "Unknown metric given as argument!"
logger.warning("Start")
print "Start"
matrix = ofile("matrix-20140601.lst")
logger.warning("Matrix loaded!")
print "Matrix loaded!"
matrix = zip(*matrix)
logger.warning("Matrix represented as floats!")
print "Matrix represented as floats!"
# similarity_mtx = create_similarity_matrix(matrix)
similarity_mtx = pdist(matrix, metric)
logger.warning("Distances calculated!")
print "Distances calculated!"
logger.addHandler(hdlr)
logger.setLevel(logging.WARNING)
metric = 'euclidean'
try:
metric = sys.argv[1]
print metric
except:
logger.warning('Unknown metric given as argument!')
print 'Unknown metric given as argument!'
logger.warning('Start')
print 'Start'
matrix = ofile("matrix-20140601.lst")
logger.warning('Matrix loaded!')
print 'Matrix loaded!'
matrix = zip(*matrix)
logger.warning('Matrix represented as floats!')
print 'Matrix represented as floats!'
# similarity_mtx = create_similarity_matrix(matrix)
similarity_mtx = pdist(matrix, metric)
logger.warning('Distances calculated!')
print 'Distances calculated!'
