| import os.path | |
| import numpy as np | |
| import pandas as pd | |
| import argparse | |
| def rmsle(predictions, actuals): | |
| rmsle_confirmed = np.sqrt(np.mean((np.log1p(predictions['ConfirmedCases']) - np.log1p(actuals['ConfirmedCases'])) ** 2)) | |
| rmsle_fatalities = np.sqrt(np.mean((np.log1p(predictions['Fatalities']) - np.log1p(actuals['Fatalities'])) ** 2)) | |
| return (rmsle_confirmed + rmsle_fatalities) / 2 | |
| parser = argparse.ArgumentParser() | |
| parser.add_argument('--path', type=str, required=True) | |
| parser.add_argument('--name', type=str, required=True) | |
| parser.add_argument('--answer_file', type=str, required=True) | |
| parser.add_argument('--predict_file', type=str, required=True) | |
| parser.add_argument('--value', type=str, default="count") | |
| args = parser.parse_args() | |
| answers = pd.read_csv(os.path.join(args.path, args.name, args.answer_file)) | |
| predictions = pd.read_csv(os.path.join(args.path, args.name, args.predict_file)) | |
| performance = rmsle(predictions, answers) | |
| with open(os.path.join(args.path, args.name, "result.txt"), "w") as f: | |
| f.write(str(performance)) | |