def build_genre_dict():
f_path = forhead_path + 'u.genre'
f_content = read_file(f_path)
genre = [line.split('|') for line in f_content]
for g in genre:
g[-1] = int(g[-1][:-1])
genre_dict = dict([g[-1], g[0]] for g in genre)
return genre_dict
def build_rating_data(data_path):
f_content = read_file(data_path)
rating_data = list()
for line in f_content:
line_data = line.split(' ')
rating_data.append(
[int(line_data[0]),
int(line_data[1]),
float(line_data[2])])
return rating_data
def build_user_data():
f_path = forhead_path + 'u.user'
f_content = read_file(f_path)
user = [line.split('|')[:-1] for line in f_content]
def format_user_data(line):
line[0] = int(line[0])
line[1] = int(line[1])
return line
user_data = map(format_user_data, user)
return user_data
def build_item_data():
f_path = forhead_path + 'u.item'
f_content = read_file(f_path)
item = [line.split('|') for line in f_content]
def format_item_data(line):
line[-1] = line[-1].strip()
genre = [int(g) for g in line[5:]]
line = line[:3]
line.append(genre)
return line
item_data = map(format_item_data, item)
return item_data
def build_occupation_data():
f_path = forhead_path + 'u.occupation'
f_content = read_file(f_path)
occupation = [line[:-1] for line in f_content]
return occupation
def build_ml_data(data_path):
f_content = read_file(data_path)
ml_data = [[int(i) for i in line.split('\t')] for line in f_content]
return ml_data
def build_trust_data():
f_path = forhead_path + 'trust.txt'
f_content = read_file(f_path)
trust_data = [[int(i) for i in line.split(' ')] for line in f_content]
return trust_data
def build_rating_data(data_path):
f_content = read_file(data_path)[1:-1]
rating_data = [[int(i) for i in line.split(' ')] for line in f_content]
return rating_data