76 lines
3.0 KiB
Python
76 lines
3.0 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 de modules (modules, ressources ou SAÉ)
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Rappel: pour éviter les confusions, on appelera *poids* les coefficients d'une
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évaluation dans un module, et *coefficients* ceux utilisés pour le calcul de la
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moyenne générale d'une 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_evaluations_poids(moduleimpl_id: int, default_poids=1.0) -> pd.DataFrame:
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"""Charge poids des évaluations d'un module et retourne un dataframe
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rows = evaluations, columns = UE, value = poids (float).
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Les valeurs manquantes (évaluations sans coef vers des UE) sont
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remplies par default_poids.
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"""
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modimpl = models.ModuleImpl.query.get(moduleimpl_id)
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evaluations = models.Evaluation.query.filter_by(moduleimpl_id=moduleimpl_id).all()
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ues = modimpl.formsemestre.query_ues().all()
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ue_ids = [ue.id for ue in ues]
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evaluation_ids = [evaluation.id for evaluation in evaluations]
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df = pd.DataFrame(columns=ue_ids, index=evaluation_ids, dtype=float)
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for eval_poids in models.EvaluationUEPoids.query.join(
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models.EvaluationUEPoids.evaluation
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).filter_by(moduleimpl_id=moduleimpl_id):
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df[eval_poids.ue_id][eval_poids.evaluation_id] = eval_poids.poids
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if default_poids is not None:
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df.fillna(value=default_poids, inplace=True)
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return df
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def check_moduleimpl_conformity(
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moduleimpl, evals_poids: pd.DataFrame, modules_coefficients: pd.DataFrame
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) -> bool:
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"""Vérifie que les évaluations de ce moduleimpl sont bien conformes
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au PN.
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Un module est dit *conforme* si et seulement si la somme des poids de ses
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évaluations vers une UE de coefficient non nul est non nulle.
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"""
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module_evals_poids = evals_poids.transpose().sum(axis=1).to_numpy() != 0
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check = all(
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(modules_coefficients[moduleimpl.module.id].to_numpy() != 0)
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== module_evals_poids
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)
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return check
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