42 lines
1.6 KiB
Python
42 lines
1.6 KiB
Python
import argparse
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import quapy as qp
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from data import ResultSubmission, evaluate_submission
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import constants
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import os
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"""
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LeQua2022 Official evaluation script
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"""
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def main(args):
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if args.task in {'T1A'}:
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qp.environ['SAMPLE_SIZE'] = constants.T1A_SAMPLE_SIZE
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true_prev = ResultSubmission.load(args.true_prevalences)
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pred_prev = ResultSubmission.load(args.pred_prevalences)
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mae, mrae = evaluate_submission(true_prev, pred_prev)
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print(f'MAE: {mae:.4f}')
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print(f'MRAE: {mrae:.4f}')
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if args.output is not None:
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outdir = os.path.dirname(args.output)
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if outdir:
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os.makedirs(outdir, exist_ok=True)
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with open(args.output, 'wt') as foo:
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foo.write(f'MAE: {mae:.4f}\n')
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foo.write(f'MRAE: {mrae:.4f}\n')
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if __name__=='__main__':
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parser = argparse.ArgumentParser(description='LeQua2022 official evaluation script')
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parser.add_argument('task', metavar='TASK', type=str, choices=['T1A', 'T1B', 'T2A', 'T2B'],
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help='Task name (T1A, T1B, T2A, T2B)')
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parser.add_argument('true_prevalences', metavar='TRUE-PREV-PATH', type=str,
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help='Path of ground truth prevalence values file (.csv)')
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parser.add_argument('pred_prevalences', metavar='PRED-PREV-PATH', type=str,
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help='Path of predicted prevalence values file (.csv)')
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parser.add_argument('--output', metavar='SCORES-PATH', type=str, default=None,
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help='Path where to store the evaluation scores')
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args = parser.parse_args()
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main(args)
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