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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))
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