From: André Ribes Date: Thu, 15 Mar 2012 13:21:48 +0000 (+0100) Subject: Observers ok add new examples test006 X-Git-Tag: V6_5_0~25^2 X-Git-Url: http://git.salome-platform.org/gitweb/?a=commitdiff_plain;h=433c74d91333f6a3638a4dbdfc4e341dc0299129;p=modules%2Fadao.git Observers ok add new examples test006 --- diff --git a/configure.ac b/configure.ac index 737babc..5807867 100644 --- a/configure.ac +++ b/configure.ac @@ -126,9 +126,9 @@ AC_CONFIG_FILES([ examples/daSalome/Makefile examples/daSalome/test003_ADAO_JDC_using_scripts.comm examples/daSalome/test004_ADAO_JDC_using_scripts.comm - examples/daSalome/test004_ADAO_JDC_Observers_using_scripts.comm examples/daSalome/test005_ADAO_Operators.comm examples/daSalome/test003_bis_ADAO_JDC_using_user_data_init.comm + examples/daSalome/test006_Observers.comm examples/daSkeletons/Makefile examples/daSkeletons/External_data_definition_by_scripts/Makefile examples/daSkeletons/External_data_definition_by_scripts/ADAO_Case.comm diff --git a/examples/daSalome/Makefile.am b/examples/daSalome/Makefile.am index ee228af..3f976ea 100644 --- a/examples/daSalome/Makefile.am +++ b/examples/daSalome/Makefile.am @@ -27,12 +27,16 @@ DATA_INST = \ test003_ADAO_scripts_for_JDC.py \ test004_ADAO_JDC_using_scripts.comm \ test004_ADAO_scripts_for_JDC.py \ - test004_ADAO_JDC_Observers_using_scripts.comm \ test005_ADAO_Operators.comm \ test005_ADAO_scripts_for_JDC.py \ test003_bis_ADAO_JDC_using_user_data_init.comm \ test003_bis_ADAO_user_data_init.py \ - test003_bis_ADAO_scripts_for_JDC.py + test003_bis_ADAO_scripts_for_JDC.py \ + test006_Observers.comm \ + test006_Observers_observer_with_file.py \ + test006_Observers_init.py \ + test006_Observers_Observation_Operator.py \ + test006_Observers_var.py examplesdasalome_DATA = ${DATA_INST} @@ -43,9 +47,13 @@ EXTRA_DIST = \ test003_ADAO_scripts_for_JDC.py \ test004_ADAO_JDC_using_scripts.comm.in \ test004_ADAO_scripts_for_JDC.py \ - test004_ADAO_JDC_Observers_using_scripts.comm.in \ test005_ADAO_Operators.comm.in \ test005_ADAO_scripts_for_JDC.py \ test003_bis_ADAO_JDC_using_user_data_init.comm.in \ test003_bis_ADAO_user_data_init.py \ - test003_bis_ADAO_scripts_for_JDC.py + test003_bis_ADAO_scripts_for_JDC.py \ + test006_Observers.comm.in \ + test006_Observers_observer_with_file.py \ + test006_Observers_init.py \ + test006_Observers_Observation_Operator.py \ + test006_Observers_var.py diff --git a/examples/daSalome/test004_ADAO_JDC_Observers_using_scripts.comm.in b/examples/daSalome/test004_ADAO_JDC_Observers_using_scripts.comm.in deleted file mode 100644 index fec8c20..0000000 --- a/examples/daSalome/test004_ADAO_JDC_Observers_using_scripts.comm.in +++ /dev/null @@ -1,47 +0,0 @@ - -ASSIMILATION_STUDY(Study_name='Test', - Study_repertory='@prefix@/share/salome/adao_examples/daSalome', - Debug=0, - Algorithm='Blue', - Background=_F(INPUT_TYPE='Vector', - data=_F(FROM='Script', - SCRIPT_FILE='test004_ADAO_scripts_for_JDC.py',),), - BackgroundError=_F(INPUT_TYPE='Matrix', - data=_F(FROM='Script', - SCRIPT_FILE='test004_ADAO_scripts_for_JDC.py',),), - Observation=_F(INPUT_TYPE='Vector', - data=_F(FROM='Script', - SCRIPT_FILE='test004_ADAO_scripts_for_JDC.py',),), - ObservationError=_F(INPUT_TYPE='Matrix', - data=_F(FROM='Script', - SCRIPT_FILE='test004_ADAO_scripts_for_JDC.py',),), - ObservationOperator=_F(INPUT_TYPE='Matrix', - data=_F(FROM='Script', - SCRIPT_FILE='test004_ADAO_scripts_for_JDC.py',),), - UserPostAnalysis=_F(FROM='String', - STRING= -"""import numpy -Xa = ADD.get("Analysis").valueserie(-1) -print -print "Size of Analysis = %i"%len(Xa) -print "Min, mean, max = %8.3f, %8.3f, %8.3f"%(min(Xa),numpy.mean(Xa),max(Xa)) -print -""",), - Observers=_F(SELECTION='Analysis', - Analysis_data=_F(NodeType='pyscript', - Value= -"""print " ---> Mise en oeuvre de l'observer : affichage de la valeur courante" -print " var =",var.valueserie(-1) -print " info =",info -# -import Gnuplot -gp = Gnuplot.Gnuplot() -gp('set style data lines') -gp('set title "'+str(info)+'"') -gp.plot( Gnuplot.Data( var.valueserie(-1) ) ) -global numero -numero += 1 -filename = "image_%02i.ps"%numero -print " sauvegarde image %s" % filename -gp.hardcopy(filename=filename, color=1) -""",),),); diff --git a/examples/daSalome/test006_Observers.comm.in b/examples/daSalome/test006_Observers.comm.in new file mode 100644 index 0000000..f1b323c --- /dev/null +++ b/examples/daSalome/test006_Observers.comm.in @@ -0,0 +1,51 @@ + +ASSIMILATION_STUDY(Study_name='test_observers', + Study_repertory='@prefix@/share/salome/adao_examples/daSalome', + Debug=0, + Algorithm='3DVAR', + Background=_F(INPUT_TYPE='Vector', + data=_F(FROM='Script', + SCRIPT_FILE='test006_Observers_var.py',),), + BackgroundError=_F(INPUT_TYPE='Matrix', + data=_F(FROM='Script', + SCRIPT_FILE='test006_Observers_var.py',),), + Observation=_F(INPUT_TYPE='Vector', + data=_F(FROM='Script', + SCRIPT_FILE='test006_Observers_var.py',),), + ObservationError=_F(INPUT_TYPE='Matrix', + data=_F(FROM='Script', + SCRIPT_FILE='test006_Observers_var.py',),), + ObservationOperator=_F(INPUT_TYPE='Function', + data=_F(FROM='FunctionDict', + FUNCTIONDICT_FILE='test006_Observers_Observation_Operator.py',),), + AlgorithmParameters=_F(INPUT_TYPE='Dict', + data=_F(FROM='Script', + SCRIPT_FILE='test006_Observers_var.py',),), + UserDataInit=_F(INIT_FILE='test006_Observers_init.py', + TARGET_LIST= + ('Background','BackgroundError','Observation', + 'ObservationError','AlgorithmParameters',),), + Observers=_F(SELECTION=('CurrentState','CostFunctionJ',), + CostFunctionJ_data=_F(NodeType='pyscript', + Value= +"""print " ---> observerCost" +print " var =",var.valueserie() +print " info =",info +# +import Gnuplot +import os +try: + numero +except NameError: + numero = 0 +gp = Gnuplot.Gnuplot() +gp('set style data lines') +gp('set title "'+str(info)+'"') +gp.plot( Gnuplot.Data( var.valueserie() ) ) +filename = os.path.join("/tmp", "imageCost_%02i.ps"%numero) +print " imageCost %s"%filename +gp.hardcopy(filename=filename, color=1) +numero += 1 +""",), + CurrentState_data=_F(NodeType='userfile', + Value='test006_Observers_observer_with_file.py',),),); diff --git a/examples/daSalome/test006_Observers_Observation_Operator.py b/examples/daSalome/test006_Observers_Observation_Operator.py new file mode 100644 index 0000000..409119b --- /dev/null +++ b/examples/daSalome/test006_Observers_Observation_Operator.py @@ -0,0 +1,88 @@ +#-*-coding:iso-8859-1-*- +# Copyright (C) 2010-2011 EDF R&D +# +# This library is free software; you can redistribute it and/or +# modify it under the terms of the GNU Lesser General Public +# License as published by the Free Software Foundation; either +# version 2.1 of the License. +# +# This library is distributed in the hope that it will be useful, +# but WITHOUT ANY WARRANTY; without even the implied warranty of +# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU +# Lesser General Public License for more details. +# +# You should have received a copy of the GNU Lesser General Public +# License along with this library; if not, write to the Free Software +# Foundation, Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA +# +# See http://www.salome-platform.org/ or email : webmaster.salome@opencascade.com +# +# Author: André Ribes, andre.ribes@edf.fr, EDF R&D + +import numpy +import time +import logging +logging.info("ComputationFunctionNode: Begin") +# ============================================================================== +# Input data and parameters: all is in the required input variable +# "computation", containing for example: +# {'inputValues': [[[[0.0, 0.0, 0.0]]]], +# 'inputVarList': ['adao_default'], +# 'outputVarList': ['adao_default'], +# 'specificParameters': [{'name': 'method', 'value': 'Direct'}]} +# ============================================================================== +# +# Recovering the type of computation: "Direct", "Tangent" or "Adjoint" +# -------------------------------------------------------------------- +method = "" +for param in computation["specificParameters"]: + if param["name"] == "method": + method = param["value"] +logging.info("ComputationFunctionNode: Found method is \'%s\'"%method) +# +# Recovering the current control state X +# -------------------------------------- +Xcurrent = computation["inputValues"][0][0][0] +# +# Building explicit calculation or requiring external ones +# -------------------------------------------------------- +dimension = 3 +H = numpy.matrix(numpy.core.identity(dimension)) +# +def FunctionH( X ): + time.sleep(1) + return H * X +# +def AdjointH( (X, Y) ): + return H.T * Y +# +# The possible computations +# ------------------------- +if method == "Direct": + logging.info("ComputationFunctionNode: Direct computation") + data = FunctionH(numpy.matrix( Xcurrent ).T) +# +if method == "Tangent": + logging.info("ComputationFunctionNode: Tangent computation") + data = FunctionH(numpy.matrix( Xcurrent ).T) +# +if method == "Adjoint": + logging.info("ComputationFunctionNode: Adjoint computation") + Ycurrent = computation["inputValues"][0][0][1] + data = AdjointH((numpy.matrix( Xcurrent ).T, numpy.matrix( Ycurrent ).T)) +# +# Formatting the output +# --------------------- +logging.info("ComputationFunctionNode: Formatting the output") +it = data.flat +outputValues = [[[[]]]] +for val in it: + outputValues[0][0][0].append(val) +# +result = {} +result["outputValues"] = outputValues +result["specificOutputInfos"] = [] +result["returnCode"] = 0 +result["errorMessage"] = "" +# +logging.info("ComputationFunctionNode: End") diff --git a/examples/daSalome/test006_Observers_init.py b/examples/daSalome/test006_Observers_init.py new file mode 100644 index 0000000..054ff36 --- /dev/null +++ b/examples/daSalome/test006_Observers_init.py @@ -0,0 +1,71 @@ +#-*-coding:iso-8859-1-*- +# Copyright (C) 2010-2011 EDF R&D +# +# This library is free software; you can redistribute it and/or +# modify it under the terms of the GNU Lesser General Public +# License as published by the Free Software Foundation; either +# version 2.1 of the License. +# +# This library is distributed in the hope that it will be useful, +# but WITHOUT ANY WARRANTY; without even the implied warranty of +# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU +# Lesser General Public License for more details. +# +# You should have received a copy of the GNU Lesser General Public +# License along with this library; if not, write to the Free Software +# Foundation, Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA +# +# See http://www.salome-platform.org/ or email : webmaster.salome@opencascade.com +# +# Author: André Ribes, andre.ribes@edf.fr, EDF R&D + +import numpy + +def FunctionH( X ): + return H * X + +dimension = 3 +xt = numpy.matrix(numpy.arange(dimension)).T +Eo = numpy.matrix(numpy.random.normal(0.,1.,size=(dimension,))).T +Eb = numpy.matrix(numpy.random.normal(0.,1.,size=(dimension,))).T +H = numpy.matrix(numpy.random.normal(0.,1.,size=(dimension,dimension))) +xb = xt + Eb +yo = FunctionH( xt ) + Eo +xb = xb.A1 +yo = yo.A1 +R = numpy.matrix(numpy.core.identity(dimension)).T +B = numpy.matrix(numpy.core.identity(dimension)).T + +# +# Definition of the Background as a vector +# ---------------------------------------- +Background = xb +# +# Definition of the Observation as a vector +# ----------------------------------------- +Observation = yo +# +# Definition of the Background Error covariance as a matrix +# --------------------------------------------------------- +BackgroundError = B +# +# Definition of the Observation Error covariance as a matrix +# ---------------------------------------------------------- +ObservationError = R + +print xb +print B +print yo +print R + +# +# Definition of the init_data dictionnary +# --------------------------------------- +init_data = {} +init_data["Background"] = Background +init_data["Observation"] = Observation +init_data["BackgroundError"] = BackgroundError +init_data["ObservationError"] = ObservationError + +# Algorithm Parameters +init_data["AlgorithmParameters"] = {"Minimizer":"LBFGSB","MaximumNumberOfSteps":5} diff --git a/examples/daSalome/test006_Observers_observer_with_file.py b/examples/daSalome/test006_Observers_observer_with_file.py new file mode 100644 index 0000000..c85e5bc --- /dev/null +++ b/examples/daSalome/test006_Observers_observer_with_file.py @@ -0,0 +1,22 @@ +print " ---> observerState" +print " var =",var.valueserie(-1) +print " info =",info +# +import Gnuplot +import os + +try: + numero +except NameError: + numero = 0 + +gp = Gnuplot.Gnuplot() +gp('set style data lines') +gp('set title "'+str(info)+'"') +gp.plot( Gnuplot.Data( var.valueserie(-1) ) ) + +filename = os.path.join("/tmp", "imageState_%02i.ps"%numero) +print " imageState \"%s\""%filename + +gp.hardcopy(filename=filename, color=1) +numero += 1 diff --git a/examples/daSalome/test006_Observers_var.py b/examples/daSalome/test006_Observers_var.py new file mode 100644 index 0000000..0e32232 --- /dev/null +++ b/examples/daSalome/test006_Observers_var.py @@ -0,0 +1,42 @@ +#-*-coding:iso-8859-1-*- +# Copyright (C) 2010-2011 EDF R&D +# +# This library is free software; you can redistribute it and/or +# modify it under the terms of the GNU Lesser General Public +# License as published by the Free Software Foundation; either +# version 2.1 of the License. +# +# This library is distributed in the hope that it will be useful, +# but WITHOUT ANY WARRANTY; without even the implied warranty of +# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU +# Lesser General Public License for more details. +# +# You should have received a copy of the GNU Lesser General Public +# License along with this library; if not, write to the Free Software +# Foundation, Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA +# +# See http://www.salome-platform.org/ or email : webmaster.salome@opencascade.com +# +# Author: André Ribes, andre.ribes@edf.fr, EDF R&D + +import numpy +# +# Definition of the Background as a vector +# ---------------------------------------- +Background = init_data["Background"] +# +# Definition of the Observation as a vector +# ----------------------------------------- +Observation = init_data["Observation"] +# +# Definition of the Background Error covariance as a matrix +# --------------------------------------------------------- +BackgroundError = init_data["BackgroundError"] +# +# Definition of the Observation Error covariance as a matrix +# ---------------------------------------------------------- +ObservationError = init_data["ObservationError"] +# +# Definition of the Observation Operator as a matrix +# -------------------------------------------------- +AlgorithmParameters = init_data["AlgorithmParameters"] diff --git a/resources/ADAOSchemaCatalog.xml b/resources/ADAOSchemaCatalog.xml index c3b6987..13630ae 100644 --- a/resources/ADAOSchemaCatalog.xml +++ b/resources/ADAOSchemaCatalog.xml @@ -169,11 +169,12 @@ if has_observers: for observer_name in observers.keys(): scheduler = "" info = "" + number = str(observers[observer_name]["number"]) if "scheduler" in observers[observer_name].keys(): scheduler = observers[observer_name]["scheduler"] if "info" in observers[observer_name].keys(): - scheduler = observers[observer_name]["info"] - assim_study.addObserver(observer_name, scheduler, info) + info = observers[observer_name]["info"] + assim_study.addObserver(observer_name, scheduler, info, number) Study = assim_study ]]> @@ -353,6 +354,7 @@ for param in data["specificParameters"]: @@ -379,15 +381,7 @@ print "Entering in Observation" diff --git a/src/daSalome/daYacsIntegration/daOptimizerLoop.py b/src/daSalome/daYacsIntegration/daOptimizerLoop.py index 565cf4c..87f2f5d 100644 --- a/src/daSalome/daYacsIntegration/daOptimizerLoop.py +++ b/src/daSalome/daYacsIntegration/daOptimizerLoop.py @@ -34,10 +34,6 @@ class OptimizerHooks: def __init__(self, optim_algo): self.optim_algo = optim_algo - # Gestion du compteur - self.sample_counter = 0 - self.counter_lock = threading.Lock() - def create_sample(self, data, method): sample = pilot.StructAny_New(self.optim_algo.runtime.getTypeCode('SALOME_TYPES/ParametricInput')) @@ -57,6 +53,12 @@ class OptimizerHooks: method_name.setEltAtRank("name", "method") method_name.setEltAtRank("value", method) specificParameters.pushBack(method_name) + print self.optim_algo.has_observer + if self.optim_algo.has_observer: + obs_switch = pilot.StructAny_New(self.optim_algo.runtime.getTypeCode('SALOME_TYPES/Parameter')) + obs_switch.setEltAtRank("name", "switch_value") + obs_switch.setEltAtRank("value", "1") + specificParameters.pushBack(obs_switch) sample.setEltAtRank("specificParameters", specificParameters) # Les données @@ -133,12 +135,12 @@ class OptimizerHooks: return matrix def Direct(self, X, sync = 1): - #print "Call Direct OptimizerHooks" + print "Call Direct OptimizerHooks" if sync == 1: # 1: Get a unique sample number - self.counter_lock.acquire() - self.sample_counter += 1 - local_counter = self.sample_counter + self.optim_algo.counter_lock.acquire() + self.optim_algo.sample_counter += 1 + local_counter = self.optim_algo.sample_counter # 2: Put sample in the job pool sample = self.create_sample(X, "Direct") @@ -163,7 +165,7 @@ class OptimizerHooks: # 5: Release lock # Have to be done before but need a new implementation # of the optimizer loop - self.counter_lock.release() + self.optim_algo.counter_lock.release() return Y else: #print "sync false is not yet implemented" @@ -173,9 +175,9 @@ class OptimizerHooks: #print "Call Tangent OptimizerHooks" if sync == 1: # 1: Get a unique sample number - self.counter_lock.acquire() - self.sample_counter += 1 - local_counter = self.sample_counter + self.optim_algo.counter_lock.acquire() + self.optim_algo.sample_counter += 1 + local_counter = self.optim_algo.sample_counter # 2: Put sample in the job pool sample = self.create_sample(X, "Tangent") @@ -198,7 +200,7 @@ class OptimizerHooks: # 5: Release lock # Have to be done before but need a new implementation # of the optimizer loop - self.counter_lock.release() + self.optim_algo.counter_lock.release() return Y else: #print "sync false is not yet implemented" @@ -208,9 +210,9 @@ class OptimizerHooks: #print "Call Adjoint OptimizerHooks" if sync == 1: # 1: Get a unique sample number - self.counter_lock.acquire() - self.sample_counter += 1 - local_counter = self.sample_counter + self.optim_algo.counter_lock.acquire() + self.optim_algo.sample_counter += 1 + local_counter = self.optim_algo.sample_counter # 2: Put sample in the job pool sample = self.create_sample((X,Y), "Adjoint") @@ -235,7 +237,7 @@ class OptimizerHooks: # 5: Release lock # Have to be done before but need a new implementation # of the optimizer loop - self.counter_lock.release() + self.optim_algo.counter_lock.release() return Z else: #print "sync false is not yet implemented" @@ -248,6 +250,12 @@ class AssimilationAlgorithm_asynch(SALOMERuntime.OptimizerAlgASync): SALOMERuntime.OptimizerAlgASync.__init__(self, None) self.runtime = SALOMERuntime.getSALOMERuntime() + self.has_observer = False + + # Gestion du compteur + self.sample_counter = 0 + self.counter_lock = threading.Lock() + # Definission des types d'entres et de sorties pour le code de calcul self.tin = self.runtime.getTypeCode("SALOME_TYPES/ParametricInput") self.tout = self.runtime.getTypeCode("SALOME_TYPES/ParametricOutput") @@ -288,26 +296,107 @@ class AssimilationAlgorithm_asynch(SALOMERuntime.OptimizerAlgASync): # Set Observers for observer_name in self.da_study.observers_dict.keys(): - if observers_dict[observer_name]["scheduler"] != "": - self.ADD.setDataObserver(observer_name, HookFunction=self.obs, Scheduler = observers_dict[observer_name]["scheduler"], HookParameters = observer_name) + print "observers %s found" % observer_name + self.has_observer = True + if self.da_study.observers_dict[observer_name]["scheduler"] != "": + self.ADD.setDataObserver(observer_name, HookFunction=self.obs, Scheduler = self.da_study.observers_dict[observer_name]["scheduler"], HookParameters = observer_name) else: self.ADD.setDataObserver(observer_name, HookFunction=self.obs, HookParameters = observer_name) # Start Assimilation Study - #print "ADD analyze" + print "ADD analyze" self.ADD.analyze() # Assimilation Study is finished self.pool.destroyAll() def obs(self, var, info): - print "Hook observer called with:" - print "var %s" % var - print "inof %s" % info + print "Call observer %s" % info + sample = pilot.StructAny_New(self.runtime.getTypeCode('SALOME_TYPES/ParametricInput')) + + # Fake data + inputVarList = pilot.SequenceAny_New(self.runtime.getTypeCode("string")) + outputVarList = pilot.SequenceAny_New(self.runtime.getTypeCode("string")) + inputVarList.pushBack("a") + outputVarList.pushBack("a") + sample.setEltAtRank("inputVarList", inputVarList) + sample.setEltAtRank("outputVarList", outputVarList) + variable = pilot.SequenceAny_New(self.runtime.getTypeCode("double")) + variable_sequence = pilot.SequenceAny_New(variable.getType()) + state_sequence = pilot.SequenceAny_New(variable_sequence.getType()) + time_sequence = pilot.SequenceAny_New(state_sequence.getType()) + variable.pushBack(1.0) + variable_sequence.pushBack(variable) + state_sequence.pushBack(variable_sequence) + time_sequence.pushBack(state_sequence) + sample.setEltAtRank("inputValues", time_sequence) + + # Add observer values in specific parameters + specificParameters = pilot.SequenceAny_New(self.runtime.getTypeCode("SALOME_TYPES/Parameter")) + + # Switch Value + obs_switch = pilot.StructAny_New(self.runtime.getTypeCode('SALOME_TYPES/Parameter')) + obs_switch.setEltAtRank("name", "switch_value") + obs_switch.setEltAtRank("value", self.da_study.observers_dict[info]["number"]) + specificParameters.pushBack(obs_switch) + + # Var + var_struct = pilot.StructAny_New(self.runtime.getTypeCode('SALOME_TYPES/Parameter')) + var_struct.setEltAtRank("name", "var") + + # Remove Data Observer, so you can ... + var.removeDataObserver(self.obs) + # Pickle then ... + var_str = pickle.dumps(var) + # Add Again Data Observer + if self.da_study.observers_dict[info]["scheduler"] != "": + self.ADD.setDataObserver(info, HookFunction=self.obs, Scheduler = self.da_study.observers_dict[info]["scheduler"], HookParameters = info) + else: + self.ADD.setDataObserver(info, HookFunction=self.obs, HookParameters = info) + var_struct.setEltAtRank("value", var_str) + specificParameters.pushBack(var_struct) + + # Info + info_struct = pilot.StructAny_New(self.runtime.getTypeCode('SALOME_TYPES/Parameter')) + info_struct.setEltAtRank("name", "info") + info_struct.setEltAtRank("value", self.da_study.observers_dict[info]["info"]) + specificParameters.pushBack(info_struct) + + sample.setEltAtRank("specificParameters", specificParameters) + + self.counter_lock.acquire() + self.sample_counter += 1 + local_counter = self.sample_counter + self.pool.pushInSample(local_counter, sample) + + # Wait + import sys, traceback + try: + while 1: + self.signalMasterAndWait() + if self.isTerminationRequested(): + self.pool.destroyAll() + else: + # Get current Id + sample_id = self.pool.getCurrentId() + if sample_id == local_counter: + # 5: Release lock + # Have to be done before but need a new implementation + # of the optimizer loop + self.counter_lock.release() + break + except: + print "Exception in user code:" + print '-'*60 + traceback.print_exc(file=sys.stdout) + print '-'*60 def getAlgoResult(self): #print "getAlgoResult" self.ADD.prepare_to_pickle() + # Remove data observers cannot pickle assimilation study object + for observer_name in self.da_study.observers_dict.keys(): + self.ADD.removeDataObserver(observer_name, self.obs) result = pickle.dumps(self.da_study) return result diff --git a/src/daSalome/daYacsIntegration/daStudy.py b/src/daSalome/daYacsIntegration/daStudy.py index 8631e9b..a3407a4 100644 --- a/src/daSalome/daYacsIntegration/daStudy.py +++ b/src/daSalome/daYacsIntegration/daStudy.py @@ -69,6 +69,7 @@ class daStudy: self.ADD.setAlgorithm(choice=self.algorithm) if self.algorithm_dict != None: + print self.algorithm_dict self.ADD.setAlgorithmParameters(asDico=self.algorithm_dict) def getAssimilationStudy(self): @@ -151,10 +152,11 @@ class daStudy: elif self.ObservationOperatorType[Name] == "Function": self.FunctionObservationOperator[Name] = ObservationOperator - def addObserver(self, name, scheduler, info): + def addObserver(self, name, scheduler, info, number): self.observers_dict[name] = {} self.observers_dict[name]["scheduler"] = scheduler self.observers_dict[name]["info"] = info + self.observers_dict[name]["number"] = number def getObservers(self): return self.observers_dict