1 #-*-coding:iso-8859-1-*-
3 # Copyright (C) 2008-2014 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, PlatformInfo
25 m = PlatformInfo.SystemUsage()
28 # ==============================================================================
29 class ElementaryAlgorithm(BasicObjects.Algorithm):
31 BasicObjects.Algorithm.__init__(self, "LINEARLEASTSQUARES")
32 self.defineRequiredParameter(
33 name = "StoreInternalVariables",
36 message = "Stockage des variables internes ou intermédiaires du calcul",
38 self.defineRequiredParameter(
39 name = "StoreSupplementaryCalculations",
42 message = "Liste de calculs supplémentaires à stocker et/ou effectuer",
46 def run(self, Xb=None, Y=None, U=None, HO=None, EM=None, CM=None, R=None, B=None, Q=None, Parameters=None):
47 logging.debug("%s Lancement"%self._name)
48 logging.debug("%s Taille mémoire utilisée de %.1f Mo"%(self._name, m.getUsedMemory("M")))
50 # Paramètres de pilotage
51 # ----------------------
52 self.setParameters(Parameters)
54 # Opérateur d'observation
55 # -----------------------
56 Hm = HO["Tangent"].asMatrix(None)
57 Hm = Hm.reshape(Y.size,-1) # ADAO & check shape
58 Ha = HO["Adjoint"].asMatrix(None)
59 Ha = Ha.reshape(-1,Y.size) # ADAO & check shape
63 # Calcul de la matrice de gain et de l'analyse
64 # --------------------------------------------
65 K = (Ha * RI * Hm).I * Ha * RI
67 self.StoredVariables["Analysis"].store( Xa.A1 )
69 # Calcul de la fonction coût
70 # --------------------------
71 if self._parameters["StoreInternalVariables"] or "OMA" in self._parameters["StoreSupplementaryCalculations"]:
73 if self._parameters["StoreInternalVariables"]:
75 Jo = 0.5 * oma.T * RI * oma
76 J = float( Jb ) + float( Jo )
77 self.StoredVariables["CostFunctionJb"].store( Jb )
78 self.StoredVariables["CostFunctionJo"].store( Jo )
79 self.StoredVariables["CostFunctionJ" ].store( J )
81 # Calculs et/ou stockages supplémentaires
82 # ---------------------------------------
83 if "OMA" in self._parameters["StoreSupplementaryCalculations"]:
84 self.StoredVariables["OMA"].store( numpy.ravel(oma) )
86 logging.debug("%s Nombre d'évaluation(s) de l'opérateur d'observation direct/tangent/adjoint : %i/%i/%i"%(self._name, HO["Direct"].nbcalls()[0],HO["Tangent"].nbcalls()[0],HO["Adjoint"].nbcalls()[0]))
87 logging.debug("%s Taille mémoire utilisée de %.1f Mo"%(self._name, m.getUsedMemory("M")))
88 logging.debug("%s Terminé"%self._name)
92 # ==============================================================================
93 if __name__ == "__main__":
94 print '\n AUTODIAGNOSTIC \n'