from utils.datareader import Datareader
from utils.submitter import Submitter
from utils.post_processing import eurm_to_recommendation_list_submission
import scipy.sparse as sps
import numpy as np
from utils.post_processing import eurm_remove_seed

dr = Datareader(verbose = False, mode = "online", only_load = "False")
sb = Submitter(dr)

eurm = sps.load_npz("ensemble_per_cat_online_new_data_25_maggio.npz")

eurm_copy = eurm.copy()
eurm_copy.data = np.ones(len(eurm_copy.data))
top_pop = eurm_copy.sum(axis=0).A1

eurm[0:1000] = eurm[0:1000] + 0.1*top_pop
eurm = eurm.tocsr()



sps.save_npz("eurm_ensemble_per_cat_toppop_boosted_26_maggio", eurm)

sb.submit(recommendation_list=eurm_to_recommendation_list_submission(eurm), name="AAA_ensemble_normale_26_maggio", track="main", verify=True, gzipped=False)