2021-12-30 23:58:38 +01:00
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##############################################################################
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# ScoDoc
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2022-01-01 14:51:28 +01:00
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# Copyright (c) 1999 - 2022 Emmanuel Viennet. All rights reserved.
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2021-12-30 23:58:38 +01:00
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# See LICENSE
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##############################################################################
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"""Résultats semestres BUT
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"""
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from app.comp import moy_ue, moy_sem, inscr_mod
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2022-01-07 15:08:45 +01:00
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from app.comp.res_common import NotesTableCompat
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2021-12-30 23:58:38 +01:00
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class ResultatsSemestreBUT(NotesTableCompat):
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"""Résultats BUT: organisation des calculs"""
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_cached_attrs = NotesTableCompat._cached_attrs + (
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"modimpl_coefs_df",
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"modimpls_evals_poids",
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"sem_cube",
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)
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def __init__(self, formsemestre):
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super().__init__(formsemestre)
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if not self.load_cached():
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self.compute()
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self.store()
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def compute(self):
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"Charge les notes et inscriptions et calcule les moyennes d'UE et gen."
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(
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self.sem_cube,
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self.modimpls_evals_poids,
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self.modimpls_results,
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) = moy_ue.notes_sem_load_cube(self.formsemestre)
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self.modimpl_inscr_df = inscr_mod.df_load_modimpl_inscr(self.formsemestre)
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self.modimpl_coefs_df, _, _ = moy_ue.df_load_modimpl_coefs(
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self.formsemestre, ues=self.ues, modimpls=self.modimpls
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)
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# l'idx de la colonne du mod modimpl.id est
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# modimpl_coefs_df.columns.get_loc(modimpl.id)
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# idx de l'UE: modimpl_coefs_df.index.get_loc(ue.id)
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self.etud_moy_ue = moy_ue.compute_ue_moys_apc(
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self.sem_cube,
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self.etuds,
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self.modimpls,
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self.ues,
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self.modimpl_inscr_df,
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self.modimpl_coefs_df,
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)
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self.etud_moy_gen = moy_sem.compute_sem_moys_apc(
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self.etud_moy_ue, self.modimpl_coefs_df
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)
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self.etud_moy_gen_ranks = moy_sem.comp_ranks_series(self.etud_moy_gen)
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def get_etud_mod_moy(self, moduleimpl_id: int, etudid: int) -> float:
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"""La moyenne de l'étudiant dans le moduleimpl
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En APC, il s'agit d'une moyenne indicative sans valeur.
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Result: valeur float (peut être naN) ou chaîne "NI" (non inscrit ou DEM)
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"""
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mod_idx = self.modimpl_coefs_df.columns.get_loc(moduleimpl_id)
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etud_idx = self.etud_index[etudid]
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# moyenne sur les UE:
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return self.sem_cube[etud_idx, mod_idx].mean()
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