56 lines
2.1 KiB
Python
56 lines
2.1 KiB
Python
# -*- mode: python -*-
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# -*- coding: utf-8 -*-
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##############################################################################
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#
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# Gestion scolarite IUT
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#
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# Copyright (c) 1999 - 2021 Emmanuel Viennet. All rights reserved.
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#
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# This program is free software; you can redistribute it and/or modify
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# it under the terms of the GNU General Public License as published by
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# the Free Software Foundation; either version 2 of the License, or
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# (at your option) any later version.
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#
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# This program is distributed in the hope that it will be useful,
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# but WITHOUT ANY WARRANTY; without even the implied warranty of
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# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
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# GNU General Public License for more details.
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#
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# You should have received a copy of the GNU General Public License
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# along with this program; if not, write to the Free Software
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# Foundation, Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA
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#
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# Emmanuel Viennet emmanuel.viennet@viennet.net
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#
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##############################################################################
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"""Fonctions de calcul des moyennes d'UE
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"""
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import numpy as np
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import pandas as pd
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from app import db
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from app import models
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def df_load_ue_coefs(formation_id: int, semestre_idx: int) -> pd.DataFrame:
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"""Load coefs of all modules in formation and returns a DataFrame
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rows = UEs, columns = modules, value = coef.
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On considère toutes les UE et modules du semestre.
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Unspecified coefs (not defined in db) are set to zero.
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"""
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ues = models.UniteEns.query.filter_by(formation_id=formation_id)
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modules = models.Module.query.filter_by(formation_id=formation_id)
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ue_ids = [ue.id for ue in ues]
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module_ids = [module.id for module in modules]
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df = pd.DataFrame(columns=module_ids, index=ue_ids, dtype=float)
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for mod_coef in (
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db.session.query(models.ModuleUECoef)
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.filter(models.UniteEns.formation_id == formation_id)
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.filter(models.ModuleUECoef.ue_id == models.UniteEns.id)
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):
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df[mod_coef.module_id][mod_coef.ue_id] = mod_coef.coef
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df.fillna(value=0, inplace=True)
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return df
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