66 lines
1.7 KiB
Python
66 lines
1.7 KiB
Python
#!/usr/bin/env python
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import argparse
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from random import randint
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import pandas as pd
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import numpy as np
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ETU_CSV = "etudiants.csv"
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SUBJ_CSV = "sujets.tsv"
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#RES_CSV = "affectations.tsv"
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def main(seed):
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etu_df = pd.read_csv(ETU_CSV)
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res_df = pd.DataFrame()
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for gr in etu_df['groupe'].unique():
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gr_df = etu_df[etu_df['groupe'] == gr]
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subj_df = pd.read_csv(SUBJ_CSV, sep='\t')
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while not gr_df.empty:
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subj = subj_df.sample()
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subj_df = subj_df.drop(index=subj.index)
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n_students = min(gr_df.shape[0], 2)
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etu = gr_df.sample(n=n_students)
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gr_df = gr_df.drop(index=etu.index)
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res_df = pd.concat([
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res_df,
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etu.merge(subj, how='cross')],
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ignore_index=True)
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# Ajout des sujets non affectes
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subj_df['groupe'] = gr
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res_df = pd.concat([
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res_df,
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subj_df],
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ignore_index=True)
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res_fn = f"affectations_{seed}.tsv"
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res_df.to_csv(res_fn, sep='\t', index=False)
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print("Successfully wrote", res_fn)
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def parse_args():
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parser = argparse.ArgumentParser(
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prog='Selection de binomes et de sujets SRA2',
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description='Mange etudiants.csv et sujets.tsv, génère affectations_<seed>.tsv. '+\
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'Vous pouvez lui donner une seed avec l\'option `-s | --seed`.')
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parser.add_argument('-s', '--seed')
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args = parser.parse_args()
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seed = args.seed
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if seed is None:
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seed = randint(0, 2**32)
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np.random.seed(int(seed))
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print("Using following random seed:", seed)
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return seed
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if __name__ == '__main__':
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seed = parse_args()
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main(seed)
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