def test_alpha(number_of_users):
res = []
nums = [i for i in range(81) if i > 5 and i % 2 == 0]
members, sm_cf, sm_cb, member_to_num, m = pickle_files_for_cv_test()
users = get_users(members, number_of_users, nums)
auc_res = {}
alpha = [i / 60 for i in range(61)]
for a in alpha:
auc_res[a] = 0
start = mktime(localtime())
for u in users:
res_cv = cv(u, 2, sm_cf, sm_cb, member_to_num, m)
for tr, res_cf, res_cb in res_cv:
for a in alpha:
pre, rec, _ = precision_recall_curve(tr, (res_cf * a + (1 - a) * res_cb))
auc_value = auc(rec, pre)
auc_res[a] += auc_value
for a in alpha:
auc_res[a] /= (2 * users.__len__())
print(mktime(localtime()) - start)
y = np.zeros(alpha.__len__())
for i, a in enumerate(alpha):
y[i] = auc_res[a]
print('Ready!')
return alpha, y
def all_test():
res = test_alpha(1500)
dump('pickle_files/test_alpha.p', res)
gc.collect()
members, sm_cf, sm_cb, member_to_num, m = pickle_files_for_cv_test()
start = mktime(localtime())
res_pre_rec = test(1500, members, sm_cf, sm_cb, member_to_num, m, 0.8, 'pre')
print(mktime(localtime()) - start)
gc.collect()
dump('pickle_files/test_pre_rec.p', res_pre_rec)
del res_pre_rec
start = mktime(localtime())
gc.collect()
res_roc = test(1500, members, sm_cf, sm_cb, member_to_num, m, 0.8, 'ROC')
print(mktime(localtime()) - start)
dump('pickle_files/test_roc.p', res_roc)
return res_pre_rec
