problems*, *Bayesian estimation*, *optimal interpolation*, *mathematical
regularization*, *meta-heuristics for optimization*, *model reduction*, *data
smoothing*, etc. More details can be found in the full ADAO documentation (see
-https://www.salome-platform.org/).
+https://www.salome-platform.org/ User Documentation dedicated section).
Only the use of ADAO text programming interface (API/TUI) is introduced
here. This interface gives ability to create a calculation object in a
similar way than the case building obtained through the graphical
-interface (GUI). When one wants to elaborate "by hand" the TUI
+interface (GUI). When one wants to elaborate directly the TUI
calculation case, it is recommended to extensively use all the ADAO
module documentation, and to go back if necessary to the graphical
interface (GUI), to get all the elements allowing to correctly set the
decl_algos = ""
adao_all_names = ""
assim_study_object = daCore.Aidsm.Aidsm()
-algos_list = assim_study_object.get_available_algorithms()
+algos_list = assim_study_object._Aidsm__get_available_algorithms()
del assim_study_object
for algo_name in algos_list:
if algo_name in infos.AssimAlgos:
*Predifined name*. This key allows to choose one of the possible variants
for the main algorithm. The default variant is the original "3DVAR", and the
possible ones are
- "3DVAR" (3D Variational analysis),
+ "3DVAR" (Classical 3D Variational analysis),
"3DVAR-VAN" (3D Variational Analysis with No inversion of B),
"3DVAR-Incr" (Incremental 3DVAR),
"3DVAR-PSAS" (Physical-space Statistical Analysis Scheme for 3DVAR),
*Nom prédéfini*. Cette clé permet de choisir l'une des variantes possibles
pour l'algorithme principal. La variante par défaut est le "3DVAR" d'origine,
et les choix possibles sont
- "3DVAR" (3D Variational analysis),
+ "3DVAR" (3D Variational analysis classique),
"3DVAR-VAN" (3D Variational Analysis with No inversion of B),
"3DVAR-Incr" (Incremental 3DVAR),
"3DVAR-PSAS" (Physical-space Statistical Analysis Scheme for 3DVAR),
"3DVAR-VAN",
"3DVAR-Incr",
"3DVAR-PSAS",
- "OneCorrection",
],
listadv = [
+ "OneCorrection",
"3DVAR-Std",
"Incr3DVAR",
],
message = "Variant ou formulation de la méthode",
listval = [
"Blue",
+ ],
+ listadv = [
"OneCorrection",
],
)
message = "Variant ou formulation de la méthode",
listval = [
"ExtendedBlue",
+ ],
+ listadv = [
"OneCorrection",
],
)
message = "Variant ou formulation de la méthode",
listval = [
"KalmanFilter",
+ ],
+ listadv = [
"OneCorrection",
],
)
message = "Variant ou formulation de la méthode",
listval = [
"LinearLeastSquares",
+ ],
+ listadv = [
"OneCorrection",
],
)
message = "Variant ou formulation de la méthode",
listval = [
"NonLinearLeastSquares",
+ ],
+ listadv = [
"OneCorrection",
],
)
# -----------------------------------------------------------
- def get_available_variables(self):
+ def __get_available_variables(self):
"""
Renvoie les variables potentiellement utilisables pour l'étude,
initialement stockées comme données d'entrées ou dans les algorithmes,
variables.sort()
return variables
- def get_available_algorithms(self):
+ def __get_available_algorithms(self):
"""
Renvoie la liste des algorithmes potentiellement utilisables, identifiés
par les chaînes de caractères.
files.sort()
return files
- def get_algorithms_main_path(self):
+ def __get_algorithms_main_path(self):
"""
Renvoie le chemin pour le répertoire principal contenant les algorithmes
"""
return self.__parent
- def add_algorithms_path(self, Path=None):
+ def __add_algorithms_path(self, Path=None):
"""
Ajoute au chemin de recherche des algorithmes un répertoire dans lequel
se trouve un sous-répertoire "daAlgorithms"
self.__paths["daNumerics"] = os.path.join(parent,"daNumerics")
#
for v in self.__paths.values():
- sys.path.insert(0, v )
+ if os.path.isdir(v): sys.path.insert(0, v )
#
# Conserve en unique exemplaire chaque chemin
sys.path = uniq( sys.path )
