From: Jean-Philippe ARGAUD <jean-philippe.argaud@edf.fr>
Date: Thu, 28 May 2015 20:33:54 +0000 (+0200)
Subject: Minor source corrections for calculation precision control
X-Git-Tag: V7_6_0~4
X-Git-Url: http://git.salome-platform.org/gitweb/?a=commitdiff_plain;h=59b589cfc4d5f8fd53230bda363fe11b250bcc50;p=modules%2Fadao.git

Minor source corrections for calculation precision control
---

diff --git a/src/daComposant/daAlgorithms/Blue.py b/src/daComposant/daAlgorithms/Blue.py
index 7e05f14..069e937 100644
--- a/src/daComposant/daAlgorithms/Blue.py
+++ b/src/daComposant/daAlgorithms/Blue.py
@@ -150,6 +150,9 @@ class ElementaryAlgorithm(BasicObjects.Algorithm):
         # ---------------------------------
         if "APosterioriCovariance" in self._parameters["StoreSupplementaryCalculations"] or \
            "SimulationQuantiles"   in self._parameters["StoreSupplementaryCalculations"]:
+            if   (Y.size <= Xb.size) and (Y.size > 100): K  = B * Ha * (R + Hm * B * Ha).I
+            elif (Y.size >  Xb.size) and (Y.size > 100): K = (BI + Ha * RI * Hm).I * Ha * RI
+            else:                                        pass # K deja calcule
             A = B - K * Hm * B
             if min(A.shape) != max(A.shape):
                 raise ValueError("The %s a posteriori covariance matrix A is of shape %s, despites it has to be a squared matrix. There is an error in the observation operator, please check it."%(self._name,str(A.shape)))
diff --git a/src/daComposant/daAlgorithms/ExtendedKalmanFilter.py b/src/daComposant/daAlgorithms/ExtendedKalmanFilter.py
index f9e2c81..fdc69cc 100644
--- a/src/daComposant/daAlgorithms/ExtendedKalmanFilter.py
+++ b/src/daComposant/daAlgorithms/ExtendedKalmanFilter.py
@@ -166,8 +166,10 @@ class ElementaryAlgorithm(BasicObjects.Algorithm):
                 if Cm is not None and Un is not None: # Attention : si Cm est aussi dans H, doublon !
                     d = d - Cm * Un
             #
+            _A = R + Ht * Pn_predicted * Ha
+            _u = numpy.linalg.solve( _A , d )
+            Xn = Xn_predicted + Pn_predicted * Ha * _u
             Kn = Pn_predicted * Ha * (R + Ht * Pn_predicted * Ha).I
-            Xn = Xn_predicted + Kn * d
             Pn = Pn_predicted - Kn * Ht * Pn_predicted
             #
             self.StoredVariables["Analysis"].store( Xn.A1 )
diff --git a/src/daComposant/daAlgorithms/KalmanFilter.py b/src/daComposant/daAlgorithms/KalmanFilter.py
index d1d50b9..9695541 100644
--- a/src/daComposant/daAlgorithms/KalmanFilter.py
+++ b/src/daComposant/daAlgorithms/KalmanFilter.py
@@ -137,8 +137,10 @@ class ElementaryAlgorithm(BasicObjects.Algorithm):
                 if Cm is not None and Un is not None: # Attention : si Cm est aussi dans H, doublon !
                     d = d - Cm * Un
             #
+            _A = R + Ht * Pn_predicted * Ha
+            _u = numpy.linalg.solve( _A , d )
+            Xn = Xn_predicted + Pn_predicted * Ha * _u
             Kn = Pn_predicted * Ha * (R + Ht * Pn_predicted * Ha).I
-            Xn = Xn_predicted + Kn * d
             Pn = Pn_predicted - Kn * Ht * Pn_predicted
             #
             self.StoredVariables["Analysis"].store( Xn.A1 )