From: André Ribes <andre.ribes@edf.fr>
Date: Fri, 1 Apr 2011 07:25:53 +0000 (+0200)
Subject: Etape 1 ok
X-Git-Tag: V6_4_0rc3~56
X-Git-Url: http://git.salome-platform.org/gitweb/?a=commitdiff_plain;h=57f426122ed8758c73645f68ad673fe562ba1c8c;p=modules%2Fadao.git

Etape 1 ok
---

diff --git a/src/daSalome/daYacsIntegration/daOptimizerLoop.py b/src/daSalome/daYacsIntegration/daOptimizerLoop.py
index c36e666..edf727e 100644
--- a/src/daSalome/daYacsIntegration/daOptimizerLoop.py
+++ b/src/daSalome/daYacsIntegration/daOptimizerLoop.py
@@ -106,11 +106,8 @@ class OptimizerHooks:
       local_counter = self.sample_counter
 
       # 2: Put sample in the job pool
-      computation = {}
-      computation["method"] = "Tangent"
-      computation["data"] = X
-      computation = pickle.dumps(computation)
-      self.optim_algo.pool.pushInSample(local_counter, computation)
+      sample = self.create_sample(X, "Tangent")
+      self.optim_algo.pool.pushInSample(local_counter, sample)
 
       # 3: Wait
       while 1:
@@ -146,11 +143,8 @@ class OptimizerHooks:
       local_counter = self.sample_counter
 
       # 2: Put sample in the job pool
-      computation = {}
-      computation["method"] = "Adjoint"
-      computation["data"] = (X, Y)
-      computation = pickle.dumps(computation)
-      self.optim_algo.pool.pushInSample(local_counter, computation)
+      sample = self.create_sample(Y, "Tangent")
+      self.optim_algo.pool.pushInSample(local_counter, sample)
 
       # 3: Wait
       while 1:
diff --git a/src/tests/daSalome/test017_3DVAR_function_script.py b/src/tests/daSalome/test017_3DVAR_function_script.py
index 4a8a6b0..ce55cca 100644
--- a/src/tests/daSalome/test017_3DVAR_function_script.py
+++ b/src/tests/daSalome/test017_3DVAR_function_script.py
@@ -7,6 +7,8 @@ for param in computation["specificParameters"]:
   if param["name"] == "method":
     method = param["value"]
 print "Method found is", method
+print computation["inputValues"]
+print computation["inputValues"][0][0]
 
 dimension = 300
 H  = numpy.matrix(numpy.core.identity(dimension))
@@ -18,12 +20,12 @@ def AdjointH( (X, Y) ):
     return H.T * Y
 
 if method == "Direct":
-  result = FunctionH(computation["data"])
+  result = FunctionH(numpy.matrix(computation["inputValues"][0][0]).T)
 
 if method == "Tangent":
-  result = FunctionH(computation["data"])
+  result = FunctionH(numpy.matrix(computation["inputValues"][0][0]).T)
 
 if method == "Adjoint":
-  result = AdjointH(computation["data"])
+  result = AdjointH(numpy.matrix(computation["inputValues"][0][0]).T)
 
 print "Computation end"