Covariance checking improvement

diff --git a/src/daComposant/daCore/AssimilationStudy.py b/src/daComposant/daCore/AssimilationStudy.py
index 3e26d02ea04f40b81fe8b576e31b0a6be36b5c48..5357a6f0b15059ff3a0972d1af62265156e2a118 100644 (file)
--- a/src/daComposant/daCore/AssimilationStudy.py
+++ b/src/daComposant/daCore/AssimilationStudy.py
@@ -137,6 +137,7 @@ class AssimilationStudy:
             asEyeByVector = None,
             asCovObject   = None,
             toBeStored    = False,
+            toBeChecked   = False,
             ):
         """
         Permet de définir la covariance des erreurs d'ébauche :
@@ -159,6 +160,7 @@ class AssimilationStudy:
             asEyeByScalar = asEyeByScalar,
             asEyeByVector = asEyeByVector,
             asCovObject   = asCovObject,
+            toBeChecked   = toBeChecked,
             )
         if toBeStored:
             self.__StoredInputs["BackgroundError"] = self.__B
@@ -202,6 +204,7 @@ class AssimilationStudy:
             asEyeByVector = None,
             asCovObject   = None,
             toBeStored    = False,
+            toBeChecked   = False,
             ):
         """
         Permet de définir la covariance des erreurs d'observations :
@@ -224,6 +227,7 @@ class AssimilationStudy:
             asEyeByScalar = asEyeByScalar,
             asEyeByVector = asEyeByVector,
             asCovObject   = asCovObject,
+            toBeChecked   = toBeChecked,
             )
         if toBeStored:
             self.__StoredInputs["ObservationError"] = self.__R
@@ -430,6 +434,7 @@ class AssimilationStudy:
             asEyeByVector = None,
             asCovObject   = None,
             toBeStored    = False,
+            toBeChecked   = False,
             ):
         """
         Permet de définir la covariance des erreurs de modèle :
@@ -452,6 +457,7 @@ class AssimilationStudy:
             asEyeByScalar = asEyeByScalar,
             asEyeByVector = asEyeByVector,
             asCovObject   = asCovObject,
+            toBeChecked   = toBeChecked,
             )
         if toBeStored:
             self.__StoredInputs["EvolutionError"] = self.__Q

diff --git a/src/daComposant/daCore/BasicObjects.py b/src/daComposant/daCore/BasicObjects.py
index 69aace219b5b91c59e6d20462cc92f9e90a27493..57d4e4101a456ce28f82eabfe90909c139f52695 100644 (file)
--- a/src/daComposant/daCore/BasicObjects.py
+++ b/src/daComposant/daCore/BasicObjects.py
@@ -510,6 +510,7 @@ class Covariance:
             asEyeByScalar = None,
             asEyeByVector = None,
             asCovObject   = None,
+            toBeChecked   = False,
             ):
         """
         Permet de définir une covariance :
@@ -525,8 +526,11 @@ class Covariance:
           methodes obligatoires "getT", "getI", "diag", "trace", "__add__",
           "__sub__", "__neg__", "__mul__", "__rmul__" et facultatives "shape",
           "size", "cholesky", "choleskyI", "asfullmatrix", "__repr__", "__str__"
+        - toBeChecked : booléen indiquant si le caractère SDP de la matrice
+          pleine doit être vérifié
         """
         self.__name       = str(name)
+        self.__check      = bool(toBeChecked)
         #
         self.__C          = None
         self.__is_scalar  = False
@@ -577,11 +581,16 @@ class Covariance:
             raise ValueError("The \"%s\" covariance matrix is not positive-definite. Please check your scalar input %s."%(self.__name,self.__C))
         if self.isvector() and (self.__C <= 0).any():
             raise ValueError("The \"%s\" covariance matrix is not positive-definite. Please check your vector input."%(self.__name,))
-        if self.ismatrix() and logging.getLogger().level < logging.WARNING: # La verification n'a lieu qu'en debug
+        if self.ismatrix() and (self.__check or logging.getLogger().level < logging.WARNING):
             try:
                 L = numpy.linalg.cholesky( self.__C )
             except:
                 raise ValueError("The %s covariance matrix is not symmetric positive-definite. Please check your matrix input."%(self.__name,))
+        if self.isobject() and (self.__check or logging.getLogger().level < logging.WARNING):
+            try:
+                L = self.__C.cholesky()
+            except:
+                raise ValueError("The %s covariance object is not symmetric positive-definite. Please check your matrix input."%(self.__name,))
 
     def isscalar(self):
         return self.__is_scalar