#
for k in self.StoredVariables:
self.__canonical_stored_name[k.lower()] = k
+ #
+ for k, v in self.__variable_names_not_public.items():
+ self.__canonical_parameter_name[k.lower()] = k
+ self.__canonical_parameter_name["algorithm"] = "Algorithm"
+ self.__canonical_parameter_name["storesupplementarycalculations"] = "StoreSupplementaryCalculations"
def _pre_run(self, Parameters, Xb=None, Y=None, R=None, B=None, Q=None ):
"Pré-calcul"
logging.debug("%s Lancement", self._name)
- logging.debug("%s Taille mémoire utilisée de %.0f Mio", self._name, self._m.getUsedMemory("Mio"))
- #
- # Mise a jour de self._parameters avec Parameters
- self.__setParameters(Parameters)
+ logging.debug("%s Taille mémoire utilisée de %.0f Mio"%(self._name, self._m.getUsedMemory("Mio")))
#
+ # Mise a jour des paramètres internes avec le contenu de Parameters, en
+ # reprenant les valeurs par défauts pour toutes celles non définies
+ self.__setParameters(Parameters, reset=True)
for k, v in self.__variable_names_not_public.items():
if k not in self._parameters: self.__setParameters( {k:v} )
#
- # Corrections et complements
+ # Corrections et compléments
def __test_vvalue(argument, variable, argname):
if argument is None:
if variable in self.__required_inputs["RequiredInputValues"]["mandatory"]:
raise ValueError("The value '%s' is not allowed for the parameter named '%s', it has to be in the list %s."%(v, __k, listval))
elif __val not in listval:
raise ValueError("The value '%s' is not allowed for the parameter named '%s', it has to be in the list %s."%( __val, __k,listval))
+ #
return __val
def requireInputArguments(self, mandatory=(), optional=()):
self.__required_inputs["RequiredInputValues"]["mandatory"] = tuple( mandatory )
self.__required_inputs["RequiredInputValues"]["optional"] = tuple( optional )
- def __setParameters(self, fromDico={}):
+ def __setParameters(self, fromDico={}, reset=False):
"""
Permet de stocker les paramètres reçus dans le dictionnaire interne.
"""
self._parameters.update( fromDico )
+ __inverse_fromDico_keys = {}
+ for k in fromDico.keys():
+ if k.lower() in self.__canonical_parameter_name:
+ __inverse_fromDico_keys[self.__canonical_parameter_name[k.lower()]] = k
+ #~ __inverse_fromDico_keys = dict([(self.__canonical_parameter_name[k.lower()],k) for k in fromDico.keys()])
+ __canonic_fromDico_keys = __inverse_fromDico_keys.keys()
for k in self.__required_parameters.keys():
- if k in fromDico.keys():
- self._parameters[k] = self.setParameterValue(k,fromDico[k])
- else:
+ if k in __canonic_fromDico_keys:
+ self._parameters[k] = self.setParameterValue(k,fromDico[__inverse_fromDico_keys[k]])
+ elif reset:
self._parameters[k] = self.setParameterValue(k)
+ else:
+ pass
logging.debug("%s %s : %s", self._name, self.__required_parameters[k]["message"], self._parameters[k])
# ==============================================================================
--- /dev/null
+# -*- coding: utf-8 -*-
+#
+# Copyright (C) 2008-2019 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: Jean-Philippe Argaud, jean-philippe.argaud@edf.fr, EDF R&D
+"Verification d'un exemple de la documentation"
+
+import sys, os, tempfile
+import unittest
+
+# ==============================================================================
+class Test_Adao(unittest.TestCase):
+ def test1(self):
+ """Test"""
+ from numpy import array, matrix
+ from adao import adaoBuilder
+ #-----------------------------------------------------------------------
+ # Analyse avec les paramètres de casse correcte
+ print("\nCase 1")
+ case = adaoBuilder.New()
+ case.set( 'AlgorithmParameters', Algorithm='3DVAR' )
+ case.set( 'AlgorithmParameters',
+ Algorithm = '3DVAR',
+ Parameters = {
+ "Minimizer":"CG",
+ "MaximumNumberOfSteps":3,
+ "CostDecrementTolerance":1.e-2,
+ "SetSeed":1234567,
+ "StoreSupplementaryCalculations":[
+ "CostFunctionJAtCurrentOptimum",
+ "SimulatedObservationAtCurrentOptimum",
+ ],
+ }
+ )
+ case.set( 'Background', Vector=[0, 1, 2] )
+ case.set( 'BackgroundError', ScalarSparseMatrix=1.0 )
+ case.set( 'Observation', Vector=array([0.5, 1.5, 2.5]) )
+ case.set( 'ObservationError', DiagonalSparseMatrix='1 1 1' )
+ case.set( 'ObservationOperator', Matrix='1 0 0;0 2 0;0 0 3' )
+ case.set( 'Observer', Variable="CostFunctionJAtCurrentOptimum", Template="ValuePrinter" )
+ case.set( 'Observer', Variable="Analysis", Template="ValuePrinter" )
+ case.execute()
+ xa1 = case.get("Analysis")[-1]
+ del case
+ #
+ #-----------------------------------------------------------------------
+ # Analyse avec les paramètres de casse quelconque
+ print("\nCase 2")
+ case = adaoBuilder.New()
+ case.set( 'AlgorithmParameters',
+ Algorithm = '3DVAR',
+ Parameters = {
+ "MINIMIZER":"CG",
+ "maximumnumberofsteps":3,
+ "COSTDecrementTOLERANCE":1.e-2,
+ "STORESUPPLEMENTARYCALCULATIONS":[
+ "CostFunctionJAtCurrentOptimum",
+ "SimulatedObservationAtCurrentOptimum",
+ ],
+ }
+ )
+ case.set( 'Background', Vector=[0, 1, 2] )
+ case.set( 'BackgroundError', ScalarSparseMatrix=1.0 )
+ case.set( 'Observation', Vector=array([0.5, 1.5, 2.5]) )
+ case.set( 'ObservationError', DiagonalSparseMatrix='1 1 1' )
+ case.set( 'ObservationOperator', Matrix='1 0 0;0 2 0;0 0 3' )
+ case.set( 'Observer', Variable="CostFunctionJAtCurrentOptimum", Template="ValuePrinter" )
+ case.set( 'Observer', Variable="Analysis", Template="ValuePrinter" )
+ case.execute()
+ xa2 = case.get("Analysis")[-1]
+ del case
+ #
+ #-----------------------------------------------------------------------
+ ecart = assertAlmostEqualArrays(xa1, xa2, places = 15)
+ #
+ print("\nTest correct")
+
+# ==============================================================================
+def filesize(name):
+ statinfo = os.stat(name)
+ return statinfo.st_size # Bytes
+
+def assertAlmostEqualArrays(first, second, places=7, msg=None, delta=None):
+ "Compare two vectors, like unittest.assertAlmostEqual"
+ import numpy
+ if msg is not None:
+ print(msg)
+ if delta is not None:
+ if ( numpy.abs(numpy.asarray(first) - numpy.asarray(second)) > float(delta) ).any():
+ raise AssertionError("%s != %s within %s places"%(first,second,delta))
+ else:
+ if ( numpy.abs(numpy.asarray(first) - numpy.asarray(second)) > 10**(-int(places)) ).any():
+ raise AssertionError("%s != %s within %i places"%(first,second,places))
+ return max(abs(numpy.asarray(first) - numpy.asarray(second)))
+
+# ==============================================================================
+if __name__ == "__main__":
+ print('\nAUTODIAGNOSTIC\n')
+ sys.stderr = sys.stdout
+ unittest.main(verbosity=2)
