def binary_accuracy_indirect(predict, true):
pred = utils.get_all_dangerous_scenarios(predict['speed'],
predict['cos_wind_dir'],
predict['sin_wind_dir'])
true = utils.get_all_dangerous_scenarios(true['speed'],
true['cos_wind_dir'],
true['sin_wind_dir'])
pred_auc = metrics.roc_auc_score(true, pred).round(3)
return pred_auc #, base_auc, pred_score, base_score,
def binary_accuracy(predict, true, baseline):
pred = utils.get_all_dangerous_scenarios(predict['speed'],
predict['cos_wind_dir'],
predict['sin_wind_dir'])
true = utils.get_all_dangerous_scenarios(true['speed'],
true['cos_wind_dir'],
true['sin_wind_dir'])
base = utils.get_all_dangerous_scenarios(baseline['speed'],
baseline['cos_wind_dir'],
baseline['sin_wind_dir'])
#calculate prediction accuracies
pred_score = metrics.accuracy_score(pred, true).round(3)
base_score = metrics.accuracy_score(base, true).round(3)
#calculate auc
pred_auc = metrics.roc_auc_score(pred, true).round(3)
base_auc = metrics.roc_auc_score(base, true).round(3)
return pred_score, base_score, pred_auc, base_auc
}
# predict_train, predict_test = run_rf(steps_in=1, steps_out=1)
for t in t_list:
#run model
predict_train, predict_test = run_rf(steps_in, steps_out=t)
# #calculate angles from sin and cosine
# predict['angle'] = predict.apply(lambda row: utils.get_angle_in_degree(row['cos_wind_dir'],row['sin_wind_dir']),axis = 1)
# true['angle'] = true.apply(lambda row: utils.get_angle_in_degree(row['cos_wind_dir'],row['sin_wind_dir']), axis = 1)
# base['angle'] = base.apply(lambda row: utils.get_angle_in_degree(row['cos_wind_dir'],row['sin_wind_dir']), axis = 1)
predict_train[
'dangerous_indirect'] = utils.get_all_dangerous_scenarios(
predict_train['speed'], predict_train['cos_wind_dir'],
predict_train['sin_wind_dir'])
predict_test['dangerous_indirect'] = utils.get_all_dangerous_scenarios(
predict_test['speed'], predict_test['cos_wind_dir'],
predict_test['sin_wind_dir'])
predict_train.to_csv('results/rf_result_train_' + str(t) + '.csv',
index=False)
predict_test.to_csv('results/rf_result_test_' + str(t) + '.csv',
index=False)
# # #calculate mae for regression
# mae_speed, mae_speed_base, mae_angle, mae_angle_base = get_mae_indirect(predict, true, base)
# #calculate accuracy & auc for scenario prediction
# pred_scenario_indirect = scenario_accuracy_indirect(predict, true)
# pred_dangerous_indirect= binary_accuracy_indirect(predict, true)