Improvements of SALOME tests

diff --git a/test/test6702/Doc_TUI_Exemple_02.py b/test/test6702/Doc_TUI_Exemple_02.py
index 3cfe935e3f9e53b7f47dcf2ee53bb0331756af51..8bc9f8aa94d6a8548f5be72b17f949750c48e4cc 100644 (file)
--- a/test/test6702/Doc_TUI_Exemple_02.py
+++ b/test/test6702/Doc_TUI_Exemple_02.py
@@ -63,10 +63,10 @@ def test2():
     #
     return case.get("Analysis")[-1]
 
-def almost_equal_vectors(v1, v2):
+def almost_equal_vectors(v1, v2, precision = 1.e-15, msg = ""):
     """Comparaison de deux vecteurs"""
-    print "\nMaximum of differences between the two :",max(abs(v2 - v1))
-    return max(abs(v2 - v1)) < 1.e-15
+    print "  Difference maximale %s: %.2e"%(msg, max(abs(v2 - v1)))
+    return max(abs(v2 - v1)) < precision
 
 # ==============================================================================
 if __name__ == "__main__":
@@ -79,4 +79,4 @@ if __name__ == "__main__":
     """
     xa1 = test1()
     xa2 = test2()
-    assert almost_equal_vectors( xa1, xa2 )
+    assert almost_equal_vectors( xa1, xa2, msg = "entre les deux" )

diff --git a/test/test6901/Verification_des_Assimilation_Algorithms.py b/test/test6901/Verification_des_Assimilation_Algorithms.py
index 17ae290a9a9f73bb1276ae3eec2fcd32bd037c4a..30a23942c4abbee10bce59362de6fcb5ba5578b8 100644 (file)
--- a/test/test6901/Verification_des_Assimilation_Algorithms.py
+++ b/test/test6901/Verification_des_Assimilation_Algorithms.py
@@ -25,6 +25,7 @@
 import adaoBuilder, numpy
 def test1():
     """Verification de la disponibilite de l'ensemble des algorithmes"""
+    Xa = {}
     for algo in ("3DVAR", "Blue", "ExtendedBlue", "LinearLeastSquares", "NonLinearLeastSquares", ):
         print
         msg = "Algorithme en test : %s"%algo
@@ -39,6 +40,7 @@ def test1():
         adaopy.setObservationOperator(Matrix = "1 0 0;0 2 0;0 0 3")
         adaopy.setObserver("Analysis",Template="ValuePrinter")
         adaopy.execute()
+        Xa[algo] = adaopy.get("Analysis")[-1]
         del adaopy
     #
     for algo in ("ExtendedKalmanFilter", "KalmanFilter", "UnscentedKalmanFilter", "4DVAR"):
@@ -57,6 +59,7 @@ def test1():
         adaopy.setEvolutionError     (ScalarSparseMatrix = 1.)
         adaopy.setObserver("Analysis",Template="ValuePrinter")
         adaopy.execute()
+        Xa[algo] = adaopy.get("Analysis")[-1]
         del adaopy
     #
     for algo in ("ParticleSwarmOptimization", "QuantileRegression", ):
@@ -75,6 +78,7 @@ def test1():
         adaopy.setEvolutionError     (ScalarSparseMatrix = 1.)
         adaopy.setObserver("Analysis",Template="ValuePrinter")
         adaopy.execute()
+        Xa[algo] = adaopy.get("Analysis")[-1]
         del adaopy
     #
     for algo in ("EnsembleBlue", ):
@@ -95,8 +99,29 @@ def test1():
         adaopy.execute()
         del adaopy
     #
+    print
+    msg = "Tests des ecarts"
+    print msg+"\n"+"="*len(msg)
+    verify_similarity_of_algo_results(("3DVAR", "Blue", "ExtendedBlue"), Xa)
+    verify_similarity_of_algo_results(("LinearLeastSquares", "NonLinearLeastSquares"), Xa)
+    verify_similarity_of_algo_results(("ExtendedKalmanFilter", "KalmanFilter", "UnscentedKalmanFilter"), Xa)
+    print
+    #
     return 0
 
+def almost_equal_vectors(v1, v2, precision = 1.e-15, msg = ""):
+    """Comparaison de deux vecteurs"""
+    print "  Difference maximale %s: %.2e"%(msg, max(abs(v2 - v1)))
+    return max(abs(v2 - v1)) < precision
+
+def verify_similarity_of_algo_results(serie = [], Xa = {}):
+    print "Camparaisons :"
+    for algo1 in serie:
+        for algo2 in serie:
+            if algo1 is algo2: break
+            assert almost_equal_vectors( Xa[algo1], Xa[algo2], 1.e-5, "entre %s et %s "%(algo1, algo2) )
+    print "Algorithmes dont les resultats sont similaires : %s\n"%(serie,)
+
 #===============================================================================
 if __name__ == "__main__":
     print '\n AUTODIAGNOSTIC \n'