From: Jean-Philippe ARGAUD <jean-philippe.argaud@edf.fr>
Date: Wed, 20 Mar 2013 09:38:48 +0000 (+0100)
Subject: Adding function checker
X-Git-Tag: V7_1_0~2
X-Git-Url: http://git.salome-platform.org/gitweb/?a=commitdiff_plain;h=0185544ad350dc66d0a7ff3f7a796ca2e6536771;p=modules%2Fadao.git

Adding function checker
---

diff --git a/src/daComposant/daAlgorithms/FunctionTest.py b/src/daComposant/daAlgorithms/FunctionTest.py
new file mode 100644
index 0000000..d99cead
--- /dev/null
+++ b/src/daComposant/daAlgorithms/FunctionTest.py
@@ -0,0 +1,102 @@
+#-*-coding:iso-8859-1-*-
+#
+#  Copyright (C) 2008-2013 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
+
+import logging
+from daCore import BasicObjects, PlatformInfo
+m = PlatformInfo.SystemUsage()
+
+import numpy
+
+# ==============================================================================
+class ElementaryAlgorithm(BasicObjects.Algorithm):
+    def __init__(self):
+        BasicObjects.Algorithm.__init__(self, "FUNCTIONTEST")
+        self.defineRequiredParameter(
+            name     = "ResultTitle",
+            default  = "",
+            typecast = str,
+            message  = "Titre du tableau et de la figure",
+            )
+
+    def run(self, Xb=None, Y=None, U=None, HO=None, EM=None, CM=None, R=None, B=None, Q=None, Parameters=None):
+        logging.debug("%s Lancement"%self._name)
+        logging.debug("%s Taille mémoire utilisée de %.1f Mo"%(self._name, m.getUsedMemory("M")))
+        #
+        # Paramètres de pilotage
+        # ----------------------
+        self.setParameters(Parameters)
+        #
+        # Opérateur d'observation
+        # -----------------------
+        Hm = HO["Direct"].appliedTo
+        #
+        # Calcul du point nominal
+        # -----------------------
+        Xn = numpy.asmatrix(numpy.ravel( Xb )).T
+        #
+        # Test
+        # ----
+        if len(self._parameters["ResultTitle"]) > 0:
+            msg  = "     ====" + "="*len(self._parameters["ResultTitle"]) + "====\n"
+            msg += "        " + self._parameters["ResultTitle"] + "\n"
+            msg += "     ====" + "="*len(self._parameters["ResultTitle"]) + "====\n"
+            print("%s"%msg)
+        #
+        msg  = "===> Information before launching:\n"
+        msg += "     -----------------------------\n"
+        msg += "     Characteristics of input parameter Xb, internally converted:\n"
+        msg += "       Type...............: %s\n"%type( Xn )
+        msg += "       Lenght of vector...: %i\n"%max(numpy.matrix( Xn ).shape)
+        msg += "       Minimum value......: %.5e\n"%numpy.min( Xn )
+        msg += "       Maximum value......: %.5e\n"%numpy.max( Xn )
+        msg += "       Mean of vector.....: %.5e\n"%numpy.mean( Xn )
+        msg += "       Standard error.....: %.5e\n"%numpy.std( Xn )
+        msg += "       L2 norm of vector..: %.5e\n"%numpy.linalg.norm( Xn )
+        print(msg)
+        #
+        CUR_LEVEL = logging.getLogger().getEffectiveLevel()
+        logging.getLogger().setLevel(logging.DEBUG)
+        print("===> Launching direct operator evaluation, activating debug\n")
+        Y = Hm( Xn )
+        print("===> End of direct operator evaluation, deactivating debug\n")
+        logging.getLogger().setLevel(CUR_LEVEL)
+        #
+        msg  = "===> Information after launching:\n"
+        msg += "     ----------------------------\n"
+        msg += "     Characteristics of output parameter Y to compare to observation:\n"
+        msg += "       Type...............: %s\n"%type( Y )
+        msg += "       Lenght of vector...: %i\n"%max(numpy.matrix( Y ).shape)
+        msg += "       Minimum value......: %.5e\n"%numpy.min( Y )
+        msg += "       Maximum value......: %.5e\n"%numpy.max( Y )
+        msg += "       Mean of vector.....: %.5e\n"%numpy.mean( Y )
+        msg += "       Standard error.....: %.5e\n"%numpy.std( Y )
+        msg += "       L2 norm of vector..: %.5e\n"%numpy.linalg.norm( Y )
+        print(msg)
+        #
+        logging.debug("%s Taille mémoire utilisée de %.1f Mo"%(self._name, m.getUsedMemory("M")))
+        logging.debug("%s Terminé"%self._name)
+        #
+        return 0
+
+# ==============================================================================
+if __name__ == "__main__":
+    print '\n AUTODIAGNOSTIC \n'
diff --git a/src/daSalome/daYacsSchemaCreator/infos_daComposant.py b/src/daSalome/daYacsSchemaCreator/infos_daComposant.py
index 4c27eba..757be83 100644
--- a/src/daSalome/daYacsSchemaCreator/infos_daComposant.py
+++ b/src/daSalome/daYacsSchemaCreator/infos_daComposant.py
@@ -67,6 +67,7 @@ AssimAlgos = [
     "ParticleSwarmOptimization",
     ]
 CheckAlgos = [
+    "FunctionTest",
     "GradientTest",
     "AdjointTest",
     ]
@@ -120,6 +121,10 @@ AlgoDataRequirements["QuantileRegression"] = [
     "ObservationOperator",
     ]
 
+AlgoDataRequirements["FunctionTest"] = [
+    "CheckingPoint",
+    "ObservationOperator",
+    ]
 AlgoDataRequirements["GradientTest"] = [
     "CheckingPoint",
     "ObservationOperator",