forked from ScoDoc/ScoDoc
Revert "Fix: calcul moy. gen. classique si aucun coef (mauvaise gestion du NaN)."
This reverts commit 15aa786ddb
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15aa786ddb
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@ -38,8 +38,8 @@ from app.comp import moy_mod
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from app.models.formsemestre import FormSemestre
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from app.models.formsemestre import FormSemestre
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from app.scodoc import sco_codes_parcours
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from app.scodoc import sco_codes_parcours
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from app.scodoc import sco_preferences
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from app.scodoc import sco_preferences
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from app.scodoc.sco_codes_parcours import NOTES_TOLERANCE, UE_SPORT
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from app.scodoc.sco_codes_parcours import UE_SPORT
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from app.scodoc.sco_utils import NOTES_PRECISION, ModuleType
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from app.scodoc.sco_utils import ModuleType
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def df_load_module_coefs(formation_id: int, semestre_idx: int = None) -> pd.DataFrame:
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def df_load_module_coefs(formation_id: int, semestre_idx: int = None) -> pd.DataFrame:
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@ -358,12 +358,10 @@ def compute_ue_moys_classic(
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)
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)
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# nb_ue x nb_etuds x nb_mods : coefs prenant en compte NaN et inscriptions
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# nb_ue x nb_etuds x nb_mods : coefs prenant en compte NaN et inscriptions
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coefs = (modimpl_coefs_etuds_no_nan_stacked * ue_modules).swapaxes(1, 2)
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coefs = (modimpl_coefs_etuds_no_nan_stacked * ue_modules).swapaxes(1, 2)
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# Ici c'est une division apr un scalaire, pas NumPy: il faut tester
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with np.errstate(invalid="ignore"): # ignore les 0/0 (-> NaN)
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sum_coefs = np.sum(coefs, axis=2)
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etud_moy_ue = (
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if abs(sum_coefs) > NOTES_PRECISION:
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np.sum(coefs * sem_matrix_inscrits, axis=2) / np.sum(coefs, axis=2)
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etud_moy_ue = (np.sum(coefs * sem_matrix_inscrits, axis=2) / sum_coefs).T
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).T
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else:
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etud_moy_ue = np.nan
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etud_moy_ue_df = pd.DataFrame(
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etud_moy_ue_df = pd.DataFrame(
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etud_moy_ue, index=modimpl_inscr_df.index, columns=[ue.id for ue in ues]
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etud_moy_ue, index=modimpl_inscr_df.index, columns=[ue.id for ue in ues]
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)
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)
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