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import os.path
import numpy as np
import pandas as pd
import argparse
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="yield")
args = parser.parse_args()
# Compute MAE
def mean_absolute_error(y_true, y_pred):
return np.mean(np.abs(y_pred - y_true))
answers = pd.read_csv( args.answer_file)
predictions = pd.read_csv( args.predict_file)
performance = mean_absolute_error(answers[args.value], predictions[args.value])
with open(os.path.join(args.path, args.name, "result.txt"), "w") as f:
f.write(str(performance))
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