From: Jean-Philippe ARGAUD <jean-philippe.argaud@edf.fr>
Date: Mon, 1 Feb 2021 20:36:31 +0000 (+0100)
Subject: Minor improvements for internal variables
X-Git-Tag: V9_7_0b1~37
X-Git-Url: http://git.salome-platform.org/gitweb/?a=commitdiff_plain;h=bf8d666f061786b6f4c4645a4c34b195ebdaf02f;p=modules%2Fadao.git

Minor improvements for internal variables
---

diff --git a/src/daComposant/daCore/BasicObjects.py b/src/daComposant/daCore/BasicObjects.py
index 76fd292..0cc2cb0 100644
--- a/src/daComposant/daCore/BasicObjects.py
+++ b/src/daComposant/daCore/BasicObjects.py
@@ -224,7 +224,8 @@ class Operator(object):
                 else:
                     if self.__Matrix is not None:
                         self.__addOneMatrixCall()
-                        _hv = self.__Matrix * xv
+                        _xv = numpy.matrix(numpy.ravel(xv)).T
+                        _hv = self.__Matrix * _xv
                     else:
                         self.__addOneMethodCall()
                         _xserie.append( xv )
@@ -272,6 +273,7 @@ class Operator(object):
             _HxValue = []
             for paire in _xuValue:
                 _xValue, _uValue = paire
+                _xValue = numpy.matrix(numpy.ravel(_xValue)).T
                 self.__addOneMatrixCall()
                 _HxValue.append( self.__Matrix * _xValue )
         else:
@@ -318,6 +320,7 @@ class Operator(object):
             _HxValue = []
             for paire in _nxValue:
                 _xNominal, _xValue = paire
+                _xValue = numpy.matrix(numpy.ravel(_xValue)).T
                 self.__addOneMatrixCall()
                 _HxValue.append( self.__Matrix * _xValue )
         else:
diff --git a/src/daComposant/daCore/NumericObjects.py b/src/daComposant/daCore/NumericObjects.py
index 1e97bf6..6ae0705 100644
--- a/src/daComposant/daCore/NumericObjects.py
+++ b/src/daComposant/daCore/NumericObjects.py
@@ -508,8 +508,24 @@ def mmqr(
     return variables, Ecart, [n,p,iteration,increment,0]
 
 # ==============================================================================
-def BackgroundEnsembleGeneration( _bgcenter, _bgcovariance, _nbmembers, _withSVD = True):
-    "Génération d'un ensemble d'ébauches aléatoires de taille _nbmembers-1"
+def EnsembleOfCenteredPerturbations( _bgcenter, _bgcovariance, _nbmembers ):
+    "Génération d'un ensemble de taille _nbmembers-1 d'états aléatoires centrés"
+    #
+    _bgcenter = numpy.ravel(_bgcenter)[:,None]
+    if _nbmembers < 1:
+        raise ValueError("Number of members has to be strictly more than 1 (given number: %s)."%(str(_nbmembers),))
+    #
+    if _bgcovariance is None:
+        BackgroundEnsemble = numpy.tile( _bgcenter, _nbmembers)
+    else:
+        _Z = numpy.random.multivariate_normal(numpy.zeros(_bgcenter.size), _bgcovariance, size=_nbmembers).T
+        BackgroundEnsemble = numpy.tile( _bgcenter, _nbmembers) + _Z
+    #
+    return BackgroundEnsemble
+
+# ==============================================================================
+def EnsembleOfBackgroundPerturbations( _bgcenter, _bgcovariance, _nbmembers, _withSVD = True):
+    "Génération d'un ensemble de taille _nbmembers-1 d'états aléatoires centrés"
     def __CenteredRandomAnomalies(Zr, N):
         """
         Génère une matrice de N anomalies aléatoires centrées sur Zr selon les
@@ -523,14 +539,15 @@ def BackgroundEnsembleGeneration( _bgcenter, _bgcovariance, _nbmembers, _withSVD
         Zr = numpy.dot(Q,Zr)
         return Zr.T
     #
+    _bgcenter = numpy.ravel(_bgcenter)[:,None]
     if _nbmembers < 1:
         raise ValueError("Number of members has to be strictly more than 1 (given number: %s)."%(str(_nbmembers),))
     if _bgcovariance is None:
-        BackgroundEnsemble = numpy.tile( numpy.ravel(_bgcenter)[:,None], _nbmembers)
+        BackgroundEnsemble = numpy.tile( _bgcenter, _nbmembers)
     else:
         if _withSVD:
             U, s, V = numpy.linalg.svd(_bgcovariance, full_matrices=False)
-            _nbctl = numpy.ravel(_bgcenter).size
+            _nbctl = _bgcenter.size
             if _nbmembers > _nbctl:
                 _Z = numpy.concatenate((numpy.dot(
                     numpy.diag(numpy.sqrt(s[:_nbctl])), V[:_nbctl]),
@@ -538,20 +555,20 @@ def BackgroundEnsembleGeneration( _bgcenter, _bgcovariance, _nbmembers, _withSVD
             else:
                 _Z = numpy.dot(numpy.diag(numpy.sqrt(s[:_nbmembers-1])), V[:_nbmembers-1])
             _Zca = __CenteredRandomAnomalies(_Z, _nbmembers)
-            BackgroundEnsemble = numpy.ravel(_bgcenter)[:,None] + _Zca
+            BackgroundEnsemble = _bgcenter + _Zca
         else:
             if max(abs(_bgcovariance.flatten())) > 0:
-                _nbctl = numpy.ravel(_bgcenter).size
+                _nbctl = _bgcenter.size
                 _Z = numpy.random.multivariate_normal(numpy.zeros(_nbctl),_bgcovariance,_nbmembers-1)
                 _Zca = __CenteredRandomAnomalies(_Z, _nbmembers)
-                BackgroundEnsemble = numpy.ravel(_bgcenter)[:,None] + _Zca
+                BackgroundEnsemble = _bgcenter + _Zca
             else:
-                BackgroundEnsemble = numpy.tile( numpy.ravel(_bgcenter)[:,None], _nbmembers)
+                BackgroundEnsemble = numpy.tile( _bgcenter, _nbmembers)
     #
     return BackgroundEnsemble
 
 # ==============================================================================
-def EnsembleCenteredAnomalies( _ensemble, _optmean = None):
+def EnsembleOfAnomalies( _ensemble, _optmean = None):
     "Renvoie les anomalies centrées à partir d'un ensemble TailleEtat*NbMembres"
     if _optmean is None:
         Em = numpy.asarray(_ensemble).mean(axis=1, dtype=mfp).astype('float')[:,numpy.newaxis]