forked from ScoDoc/DocScoDoc
Divisions par zéro non controlées si les arrays vides passent en object
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@ -266,6 +266,8 @@ def compute_ue_moys_apc(
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# Annule les coefs des modules NaN
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modimpl_coefs_etuds_no_nan = np.where(np.isnan(sem_cube), 0.0, modimpl_coefs_etuds)
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if modimpl_coefs_etuds_no_nan.dtype == np.object: # arrive sur des tableaux vides
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modimpl_coefs_etuds_no_nan = modimpl_coefs_etuds_no_nan.astype(np.float)
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#
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# Version vectorisée
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#
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@ -348,7 +350,8 @@ def compute_ue_moys_classic(
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modimpl_coefs_etuds_no_nan = np.where(
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np.isnan(sem_matrix), 0.0, modimpl_coefs_etuds
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)
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if modimpl_coefs_etuds_no_nan.dtype == np.object: # arrive sur des tableaux vides
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modimpl_coefs_etuds_no_nan = modimpl_coefs_etuds_no_nan.astype(np.float)
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# --------------------- Calcul des moyennes d'UE
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ue_modules = np.array(
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[[m.module.ue == ue for m in formsemestre.modimpls_sorted] for ue in ues]
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@ -358,6 +361,8 @@ def compute_ue_moys_classic(
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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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coefs = (modimpl_coefs_etuds_no_nan_stacked * ue_modules).swapaxes(1, 2)
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if coefs.dtype == np.object: # arrive sur des tableaux vides
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coefs = coefs.astype(np.float)
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with np.errstate(invalid="ignore"): # ignore les 0/0 (-> NaN)
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etud_moy_ue = (
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np.sum(coefs * sem_matrix_inscrits, axis=2) / np.sum(coefs, axis=2)
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