--- /dev/null
+
+ASSIMILATION_STUDY(Study_name='Test',
+ Study_repertory='@prefix@/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
+""",),);
--- /dev/null
+#-*-coding:iso-8859-1-*-
+import numpy
+#
+n = 100
+#
+# Definition of the Background as a vector
+# ----------------------------------------
+Background = n * [0]
+#
+# Definition of the Observation as a vector
+# -----------------------------------------
+Observation = n * "1 "
+Observation = Observation.strip()
+#
+# Definition of the Background Error covariance as a matrix
+# ---------------------------------------------------------
+BackgroundError = numpy.identity(n)
+#
+# Definition of the Observation Error covariance as a matrix
+# ----------------------------------------------------------
+ObservationError = numpy.identity(n)
+#
+# Definition of the Observation Operator as a matrix
+# --------------------------------------------------
+ObservationOperator = numpy.identity(n)