X-Git-Url: http://git.salome-platform.org/gitweb/?a=blobdiff_plain;f=src%2FdaComposant%2FdaCore%2FTemplates.py;h=bd4ffc1d18a55905849059aff70c8d3b3149dc34;hb=e0656540c715b3fa57adb5771421935a63e5284b;hp=aa9fcc3249f2727f7d6f38583e13192da029f455;hpb=7672546d765b288764e7bcc785340c66322998bb;p=modules%2Fadao.git

diff --git a/src/daComposant/daCore/Templates.py b/src/daComposant/daCore/Templates.py
index aa9fcc3..bd4ffc1 100644
--- a/src/daComposant/daCore/Templates.py
+++ b/src/daComposant/daCore/Templates.py
@@ -1,6 +1,6 @@
 # -*- coding: utf-8 -*-
 #
-# Copyright (C) 2008-2019 EDF R&D
+# Copyright (C) 2008-2022 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
@@ -21,7 +21,7 @@
 # Author: Jean-Philippe Argaud, jean-philippe.argaud@edf.fr, EDF R&D
 
 """
-    Modèles généraux pour les observers, le post-processing
+    Modèles généraux pour les observers, le post-processing.
 """
 __author__ = "Jean-Philippe ARGAUD"
 __all__ = ["ObserverTemplates"]
@@ -59,10 +59,6 @@ class TemplateStorage(object):
         __keys = sorted(self.__values.keys())
         return __keys
 
-    # def has_key(self, name):
-    #     "D.has_key(k) -> True if D has a key k, else False"
-    #     return name in self.__values
-
     def __contains__(self, name):
         "D.__contains__(k) -> True if D has a key k, else False"
         return name in self.__values
@@ -225,6 +221,52 @@ ObserverTemplates.store(
     order   = "next",
     )
 
+# ==============================================================================
+UserPostAnalysisTemplates = TemplateStorage()
+
+UserPostAnalysisTemplates.store(
+    name    = "AnalysisPrinter",
+    content = """print('# Post-analysis')\nimport numpy\nxa=ADD.get('Analysis')[-1]\nprint('Analysis',xa)""",
+    fr_FR   = "Imprime sur la sortie standard la valeur optimale",
+    en_EN   = "Print on standard output the optimal value",
+    order   = "next",
+    )
+UserPostAnalysisTemplates.store(
+    name    = "AnalysisSaver",
+    content = """print('# Post-analysis')\nimport numpy\nxa=ADD.get('Analysis')[-1]\nf='/tmp/analysis.txt'\nprint('Analysis saved in \"%s\"'%f)\nnumpy.savetxt(f,xa)""",
+    fr_FR   = "Enregistre la valeur optimale dans un fichier du répertoire '/tmp' nommé 'analysis.txt'",
+    en_EN   = "Save the optimal value in a file of the '/tmp' directory named 'analysis.txt'",
+    order   = "next",
+    )
+UserPostAnalysisTemplates.store(
+    name    = "AnalysisPrinterAndSaver",
+    content = """print('# Post-analysis')\nimport numpy\nxa=ADD.get('Analysis')[-1]\nprint('Analysis',xa)\nf='/tmp/analysis.txt'\nprint('Analysis saved in \"%s\"'%f)\nnumpy.savetxt(f,xa)""",
+    fr_FR   = "Imprime sur la sortie standard et, en même temps enregistre dans un fichier du répertoire '/tmp', la valeur optimale",
+    en_EN   = "Print on standard output and, in the same time save in a file of the '/tmp' directory, the optimal value",
+    order   = "next",
+    )
+UserPostAnalysisTemplates.store(
+    name    = "AnalysisSeriePrinter",
+    content = """print('# Post-analysis')\nimport numpy\nxa=ADD.get('Analysis')\nprint('Analysis',xa)""",
+    fr_FR   = "Imprime sur la sortie standard la série des valeurs optimales",
+    en_EN   = "Print on standard output the optimal value series",
+    order   = "next",
+    )
+UserPostAnalysisTemplates.store(
+    name    = "AnalysisSerieSaver",
+    content = """print('# Post-analysis')\nimport numpy\nxa=ADD.get('Analysis')\nf='/tmp/analysis.txt'\nprint('Analysis saved in \"%s\"'%f)\nnumpy.savetxt(f,xa)""",
+    fr_FR   = "Enregistre la série des valeurs optimales dans un fichier du répertoire '/tmp' nommé 'analysis.txt'",
+    en_EN   = "Save the optimal value series in a file of the '/tmp' directory named 'analysis.txt'",
+    order   = "next",
+    )
+UserPostAnalysisTemplates.store(
+    name    = "AnalysisSeriePrinterAndSaver",
+    content = """print('# Post-analysis')\nimport numpy\nxa=ADD.get('Analysis')\nprint('Analysis',xa)\nf='/tmp/analysis.txt'\nprint('Analysis saved in \"%s\"'%f)\nnumpy.savetxt(f,xa)""",
+    fr_FR   = "Imprime sur la sortie standard et, en même temps enregistre dans un fichier du répertoire '/tmp', la série des valeurs optimales",
+    en_EN   = "Print on standard output and, in the same time save in a file of the '/tmp' directory, the optimal value series",
+    order   = "next",
+    )
+
 # ==============================================================================
 if __name__ == "__main__":
     print('\n AUTODIAGNOSTIC\n')