def get_title(rf_local):
# when you are asked to "shadow name", you should change the name.
x = rf_local.get_test_set_original_results()
y = rf_local.testResults
type_str = BPTypes.get_type_name(rf_local.type)
stats_toolkit_obj = StatsToolKits(x, y)
pearson_r, p_val = stats_toolkit_obj.get_pearson_corr()
mic = stats_toolkit_obj.get_mic()
return type_str + ' ' + 'Regression Results\n' + \
'pearson regression: ' + '%.2f' % pearson_r + ' p value: ' + '%.2e' % p_val + '\n'\
'maximal information coefficient: ' + '%.2f' % mic
def disp_stats_paras(rf_local):
stats_toolkit_obj = StatsToolKits([], [])
print("testset size:" + "%d" % (len(rf_local.get_test_set_original_results()) / 0.2))
print("testset range:" + "%d" % stats_toolkit_obj.get_range(rf_local.get_test_set_original_results()))
print("standard derivation:" + "%.2f" % stats_toolkit_obj.get_std(rf_local.get_test_set_original_results()))
print("sbp max index:" + str(max_sbp_index) + " ")
print(sbp_corrs)
print("dbp max index:" + str(max_dbp_index) + " ")
print(dbp_corrs)
rf = RegressionAlgorithm()
rf.x_train = full_set_arr[max_sbp_train_index, :]
rf.y_train = full_set_res[max_sbp_train_index]
rf.x_test = full_set_arr[max_sbp_test_index, :]
rf.y_test = full_set_res[max_sbp_test_index]
rf.train_mbp()
cor = rf.test()
# rf.show_full_set_result("Best SBP Regression")
rf.show_mbp_full_set_result("Best SBP Regression", list(rf.y_test))
stk = StatsToolKits(cor, full_set_res[max_sbp_test_index])
cor = stk.get_pearson_corr()
print('***************SBP CORR')
print cor
# rf.reset_model()
# rf.alter_type()
# rf.x_train = full_set_arr[max_dbp_train_index, :]
# rf.y_train = full_set_res[max_dbp_train_index, :]
# rf.x_test = full_set_arr[max_dbp_test_index, :]
# rf.y_test = full_set_res[max_dbp_test_index, :]
# rf.train()
# rf.test()
# rf.show_full_set_result("Best DBP Regression")
exit()
