From: Jean-Philippe ARGAUD <jean-philippe.argaud@edf.fr>
Date: Sun, 27 Dec 2020 06:46:24 +0000 (+0100)
Subject: Fix some coherency choices for *KF algorithms
X-Git-Tag: V9_7_0b1~57
X-Git-Url: http://git.salome-platform.org/gitweb/?a=commitdiff_plain;h=967ce0a170eafb3c7ac3f734179099117a1eb2f1;p=modules%2Fadao.git

Fix some coherency choices for *KF algorithms
---

diff --git a/src/daComposant/daAlgorithms/ExtendedKalmanFilter.py b/src/daComposant/daAlgorithms/ExtendedKalmanFilter.py
index b243668..ee838c8 100644
--- a/src/daComposant/daAlgorithms/ExtendedKalmanFilter.py
+++ b/src/daComposant/daAlgorithms/ExtendedKalmanFilter.py
@@ -140,10 +140,12 @@ class ElementaryAlgorithm(BasicObjects.Algorithm):
             if self._toStore("APosterioriCovariance"):
                 self.StoredVariables["APosterioriCovariance"].store( Pn.asfullmatrix(Xn.size) )
                 covarianceXa = Pn
+                if self._parameters["EstimationOf"] == "Parameters":
+                    covarianceXaMin = Pn
         #
-        Xa               = Xn
-        XaMin            = Xn
-        previousJMinimum = numpy.finfo(float).max
+        if self._parameters["EstimationOf"] == "Parameters":
+            XaMin            = Xn
+            previousJMinimum = numpy.finfo(float).max
         #
         for step in range(duration-1):
             if hasattr(Y,"store"):
diff --git a/src/daComposant/daAlgorithms/KalmanFilter.py b/src/daComposant/daAlgorithms/KalmanFilter.py
index eadb068..257cd26 100644
--- a/src/daComposant/daAlgorithms/KalmanFilter.py
+++ b/src/daComposant/daAlgorithms/KalmanFilter.py
@@ -131,9 +131,12 @@ class ElementaryAlgorithm(BasicObjects.Algorithm):
             if self._toStore("APosterioriCovariance"):
                 self.StoredVariables["APosterioriCovariance"].store( Pn.asfullmatrix(Xn.size) )
                 covarianceXa = Pn
+                if self._parameters["EstimationOf"] == "Parameters":
+                    covarianceXaMin = Pn
         #
-        Xa               = Xn
-        previousJMinimum = numpy.finfo(float).max
+        if self._parameters["EstimationOf"] == "Parameters":
+            XaMin            = Xn
+            previousJMinimum = numpy.finfo(float).max
         #
         for step in range(duration-1):
             if hasattr(Y,"store"):
diff --git a/src/daComposant/daAlgorithms/UnscentedKalmanFilter.py b/src/daComposant/daAlgorithms/UnscentedKalmanFilter.py
index 5af253c..4fa7d04 100644
--- a/src/daComposant/daAlgorithms/UnscentedKalmanFilter.py
+++ b/src/daComposant/daAlgorithms/UnscentedKalmanFilter.py
@@ -102,7 +102,7 @@ class ElementaryAlgorithm(BasicObjects.Algorithm):
             message  = "Liste des valeurs de bornes",
             )
         self.requireInputArguments(
-            mandatory= ("Xb", "Y", "HO", "R", "B" ),
+            mandatory= ("Xb", "Y", "HO", "R", "B"),
             optional = ("U", "EM", "CM", "Q"),
             )
         self.setAttributes(tags=(
@@ -178,14 +178,17 @@ class ElementaryAlgorithm(BasicObjects.Algorithm):
         else:                         Pn = B
         #
         if len(self.StoredVariables["Analysis"])==0 or not self._parameters["nextStep"]:
-            self.StoredVariables["Analysis"].store( numpy.ravel(Xb) )
+            self.StoredVariables["CurrentIterationNumber"].store( len(self.StoredVariables["Analysis"]) )
+            self.StoredVariables["Analysis"].store( numpy.ravel(Xn) )
             if self._toStore("APosterioriCovariance"):
                 self.StoredVariables["APosterioriCovariance"].store( Pn )
                 covarianceXa = Pn
+                if self._parameters["EstimationOf"] == "Parameters":
+                    covarianceXaMin = Pn
         #
-        Xa               = Xb
-        XaMin            = Xb
-        previousJMinimum = numpy.finfo(float).max
+        if self._parameters["EstimationOf"] == "Parameters":
+            XaMin            = Xn
+            previousJMinimum = numpy.finfo(float).max
         #
         for step in range(duration-1):
             if hasattr(Y,"store"):