1 # -*- coding: utf-8 -*-
3 # Copyright (C) 2008-2023 EDF R&D
5 # This library is free software; you can redistribute it and/or
6 # modify it under the terms of the GNU Lesser General Public
7 # License as published by the Free Software Foundation; either
8 # version 2.1 of the License.
10 # This library is distributed in the hope that it will be useful,
11 # but WITHOUT ANY WARRANTY; without even the implied warranty of
12 # MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU
13 # Lesser General Public License for more details.
15 # You should have received a copy of the GNU Lesser General Public
16 # License along with this library; if not, write to the Free Software
17 # Foundation, Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA
19 # See http://www.salome-platform.org/ or email : webmaster.salome@opencascade.com
21 # Author: Jean-Philippe Argaud, jean-philippe.argaud@edf.fr, EDF R&D
24 from daCore import BasicObjects
25 from daAlgorithms.Atoms import ecweim, ecwdeim, eosg
27 # ==============================================================================
28 class ElementaryAlgorithm(BasicObjects.Algorithm):
30 BasicObjects.Algorithm.__init__(self, "MEASUREMENTSOPTIMALPOSITIONING")
31 self.defineRequiredParameter(
35 message = "Variant ou formulation de la méthode",
37 "EIM", "PositioningByEIM",
38 "lcEIM", "PositioningBylcEIM",
39 "DEIM", "PositioningByDEIM",
40 "lcDEIM", "PositioningBylcDEIM",
43 self.defineRequiredParameter(
44 name = "EnsembleOfSnapshots",
46 typecast = numpy.array,
47 message = "Ensemble de vecteurs d'état physique (snapshots), 1 état par colonne (Training Set)",
49 self.defineRequiredParameter(
50 name = "MaximumNumberOfLocations",
53 message = "Nombre maximal de positions",
56 self.defineRequiredParameter(
57 name = "ExcludeLocations",
60 message = "Liste des indices ou noms de positions exclues selon l'ordre interne d'un snapshot",
62 self.defineRequiredParameter(
63 name = "NameOfLocations",
66 message = "Liste des noms de positions selon l'ordre interne d'un snapshot",
68 self.defineRequiredParameter(
72 message = "Norme d'erreur utilisée pour le critère d'optimalité des positions",
73 listval = ["L2", "Linf"]
75 self.defineRequiredParameter(
76 name = "ErrorNormTolerance",
79 message = "Valeur limite inférieure du critère d'optimalité forçant l'arrêt",
82 self.defineRequiredParameter(
83 name = "SampleAsnUplet",
86 message = "Points de calcul définis par une liste de n-uplet",
88 self.defineRequiredParameter(
89 name = "SampleAsExplicitHyperCube",
92 message = "Points de calcul définis par un hyper-cube dont on donne la liste des échantillonnages de chaque variable comme une liste",
94 self.defineRequiredParameter(
95 name = "SampleAsMinMaxStepHyperCube",
98 message = "Points de calcul définis par un hyper-cube dont on donne la liste des échantillonnages de chaque variable par un triplet [min,max,step]",
100 self.defineRequiredParameter(
101 name = "SampleAsIndependantRandomVariables",
104 message = "Points de calcul définis par un hyper-cube dont les points sur chaque axe proviennent de l'échantillonnage indépendant de la variable selon la spécification ['distribution',[parametres],nombre]",
106 self.defineRequiredParameter(
110 message = "Activation du mode debug lors de l'exécution",
112 self.defineRequiredParameter(
113 name = "StoreSupplementaryCalculations",
116 message = "Liste de calculs supplémentaires à stocker et/ou effectuer",
118 "EnsembleOfSimulations",
127 self.defineRequiredParameter(
129 typecast = numpy.random.seed,
130 message = "Graine fixée pour le générateur aléatoire",
132 self.requireInputArguments(
134 optional = ("Xb", "HO"),
136 self.setAttributes(tags=(
141 def run(self, Xb=None, Y=None, U=None, HO=None, EM=None, CM=None, R=None, B=None, Q=None, Parameters=None):
142 self._pre_run(Parameters, Xb, Y, U, HO, EM, CM, R, B, Q)
144 #--------------------------
145 if self._parameters["Variant"] in ["lcEIM", "PositioningBylcEIM"]:
146 if len(self._parameters["EnsembleOfSnapshots"]) > 0:
147 if self._toStore("EnsembleOfSimulations"):
148 self.StoredVariables["EnsembleOfSimulations"].store( self._parameters["EnsembleOfSnapshots"] )
149 ecweim.EIM_offline(self, self._parameters["EnsembleOfSnapshots"])
150 elif isinstance(HO, dict):
151 ecweim.EIM_offline(self, eosg.eosg(self, Xb, HO))
153 raise ValueError("Snapshots or Operator have to be given in order to launch the analysis")
155 elif self._parameters["Variant"] in ["EIM", "PositioningByEIM"]:
156 if len(self._parameters["EnsembleOfSnapshots"]) > 0:
157 if self._toStore("EnsembleOfSimulations"):
158 self.StoredVariables["EnsembleOfSimulations"].store( self._parameters["EnsembleOfSnapshots"] )
159 ecweim.EIM_offline(self, self._parameters["EnsembleOfSnapshots"])
160 elif isinstance(HO, dict):
161 ecweim.EIM_offline(self, eosg.eosg(self, Xb, HO))
163 raise ValueError("Snapshots or Operator have to be given in order to launch the analysis")
165 #--------------------------
166 elif self._parameters["Variant"] in ["lcDEIM", "PositioningBylcDEIM"]:
167 if len(self._parameters["EnsembleOfSnapshots"]) > 0:
168 if self._toStore("EnsembleOfSimulations"):
169 self.StoredVariables["EnsembleOfSimulations"].store( self._parameters["EnsembleOfSnapshots"] )
170 ecwdeim.DEIM_offline(self, self._parameters["EnsembleOfSnapshots"])
171 elif isinstance(HO, dict):
172 ecwdeim.DEIM_offline(self, eosg.eosg(self, Xb, HO))
174 raise ValueError("Snapshots or Operator have to be given in order to launch the analysis")
176 elif self._parameters["Variant"] in ["DEIM", "PositioningByDEIM"]:
177 if len(self._parameters["EnsembleOfSnapshots"]) > 0:
178 if self._toStore("EnsembleOfSimulations"):
179 self.StoredVariables["EnsembleOfSimulations"].store( self._parameters["EnsembleOfSnapshots"] )
180 ecwdeim.DEIM_offline(self, self._parameters["EnsembleOfSnapshots"])
181 elif isinstance(HO, dict):
182 ecwdeim.DEIM_offline(self, eosg.eosg(self, Xb, HO))
184 raise ValueError("Snapshots or Operator have to be given in order to launch the analysis")
186 #--------------------------
188 raise ValueError("Error in Variant name: %s"%self._parameters["Variant"])
193 # ==============================================================================
194 if __name__ == "__main__":
195 print('\n AUTODIAGNOSTIC\n')