2 # Copyright (C) 2010-2011 EDF R&D
4 # This library is free software; you can redistribute it and/or
5 # modify it under the terms of the GNU Lesser General Public
6 # License as published by the Free Software Foundation; either
7 # version 2.1 of the License.
9 # This library is distributed in the hope that it will be useful,
10 # but WITHOUT ANY WARRANTY; without even the implied warranty of
11 # MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU
12 # Lesser General Public License for more details.
14 # You should have received a copy of the GNU Lesser General Public
15 # License along with this library; if not, write to the Free Software
16 # Foundation, Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA
18 # See http://www.salome-platform.org/ or email : webmaster.salome@opencascade.com
20 # Author: André Ribes, andre.ribes@edf.fr, EDF R&D
22 from daCore.AssimilationStudy import AssimilationStudy
23 from daCore import Logging
26 class daError(Exception):
27 def __init__(self, value):
30 return repr(self.value)
34 def __init__(self, name, algorithm, debug):
36 self.ADD = AssimilationStudy(name)
37 self.ADD.setControls()
38 self.algorithm = algorithm
39 self.algorithm_dict = None
40 self.Background = None
41 self.InputVariables = {}
42 self.OutputVariables = {}
43 self.InputVariablesOrder = []
44 self.OutputVariablesOrder = []
45 self.observers_dict = {}
49 logging.getLogger().setLevel(logging.DEBUG)
51 logging.getLogger().setLevel(logging.WARNING)
53 # Observation Management
54 self.ObservationOperatorType = {}
55 self.FunctionObservationOperator = {}
57 def setInputVariable(self, name, size):
58 self.InputVariables[name] = size
59 self.InputVariablesOrder.append(name)
61 def setOutputVariable(self, name, size):
62 self.OutputVariables[name] = size
63 self.OutputVariablesOrder.append(name)
65 def setAlgorithmParameters(self, parameters):
66 self.algorithm_dict = parameters
68 def initAlgorithm(self):
70 self.ADD.setAlgorithm(choice=self.algorithm)
71 if self.algorithm_dict != None:
72 logging.debug("ADD.setAlgorithm : "+str(self.algorithm_dict))
73 self.ADD.setAlgorithmParameters(asDico=self.algorithm_dict)
75 def getAssimilationStudy(self):
79 # Methods to initialize AssimilationStudy
81 def setBackgroundType(self, Type):
84 self.BackgroundType = Type
86 raise daError("[daStudy::setBackgroundType] Type is unkown : " + Type + " Types are : Vector")
88 def setBackground(self, Background):
92 except AttributeError:
93 raise daError("[daStudy::setBackground] Type is not defined !")
95 self.Background = Background
97 if self.BackgroundType == "Vector":
98 self.ADD.setBackground(asVector = Background)
100 def getBackground(self):
101 return self.Background
103 def setBackgroundError(self, BackgroundError):
105 self.ADD.setBackgroundError(asCovariance = BackgroundError)
107 def setObservationType(self, Type):
110 self.ObservationType = Type
112 raise daError("[daStudy::setObservationType] Type is unkown : " + Type + " Types are : Vector")
114 def setObservation(self, Observation):
118 except AttributeError:
119 raise daError("[daStudy::setObservation] Type is not defined !")
121 if self.ObservationType == "Vector":
122 self.ADD.setObservation(asVector = Observation)
124 def setObservationError(self, ObservationError):
125 self.ADD.setObservationError(asCovariance = ObservationError)
128 def getObservationOperatorType(self, Name):
131 rtn = self.ObservationOperatorType[Name]
136 def setObservationOperatorType(self, Name, Type):
138 self.ObservationOperatorType[Name] = Type
139 elif Type == "Function":
140 self.ObservationOperatorType[Name] = Type
142 raise daError("[daStudy::setObservationOperatorType] Type is unkown : " + Type + " Types are : Matrix")
144 def setObservationOperator(self, Name, ObservationOperator):
146 self.ObservationOperatorType[Name]
147 except AttributeError:
148 raise daError("[daStudy::setObservationOperator] Type is not defined !")
150 if self.ObservationOperatorType[Name] == "Matrix":
151 self.ADD.setObservationOperator(asMatrix = ObservationOperator)
152 elif self.ObservationOperatorType[Name] == "Function":
153 self.FunctionObservationOperator[Name] = ObservationOperator
155 def addObserver(self, name, scheduler, info, number):
156 self.observers_dict[name] = {}
157 self.observers_dict[name]["scheduler"] = scheduler
158 self.observers_dict[name]["info"] = info
159 self.observers_dict[name]["number"] = number
161 def getObservers(self):
162 return self.observers_dict