def __init__(self, valid_repos_list, pm_dir, assessments_dir):
logging.basicConfig(filename="AvgUserSrdp_performance_"+str(time.time())+".log",level=logging.DEBUG)
self.valid_repos_list = valid_repos_list
self.NU = len(self.valid_repos_list)
self.total_positives = np.array([len(a) for a in valid_repos_list])
self.predicted_positives = np.zeros(self.NU)
self.out_dir = assessments_dir
self.fileno = 0
self.pm_dir = pm_dir
r_fn = Runner.run_results_fn(pm_dir, 0)
self.pm_repos_list = Recommender.load_recommendations(r_fn)
argparser = ArgumentParser()
argparser.add_argument('metric', help="Which metric to test among" \
"recall, unserendipity, sdist, srdp")
argparser.add_argument('recommendations_fn', help="filename of recommendations")
argparser.add_argument('G_I_ru_tm_fn', help="Interest graph (repositories, users) filename")
argparser.add_argument('vrt_fn', help="Validation repositories and times filename")
argparser.add_argument('Ks', help="Top Ks", type=int, nargs='+')
#Needed if doing sdist
argparser.add_argument('--G_F_fn', help="Followership graph (users, users) filename")
argparser.add_argument('--dir', help="Where to store the generated assessments",
default=join(os.getcwd(),"Assessments") )
argparser.add_argument('--test', help="is a test?", action="store_true")
args = argparser.parse_args()
recommendations_fn = abspath(args.recommendations_fn)
recommendations = Recommender.load_recommendations(recommendations_fn)
G_I_ru_tm_fn = abspath(args.G_I_ru_tm_fn)
G_F_fn = abspath(args.G_F_fn)
dataset_dir = dirname(G_I_ru_tm_fn)
out_dir = abspath(args.dir)
if not exists(out_dir):
os.makedirs(out_dir)
vrt_fn = abspath(args.vrt_fn)
with open(vrt_fn, "rb") as pf:
valid_times_repos_list = cPickle.load(pf)
valid_times_list = [a[0] for a in valid_times_repos_list]
valid_repos_list = [a[1] for a in valid_times_repos_list]
if args.test:
