Updating copyright date information (1)

[modules/adao.git] / src / daComposant / daAlgorithms / ExtendedKalmanFilter.py

diff --git a/src/daComposant/daAlgorithms/ExtendedKalmanFilter.py b/src/daComposant/daAlgorithms/ExtendedKalmanFilter.py
index 621cf51d0a02f2b23c4926165b8b18722dac1572..4efab27000575e4230ed6fffd38be43416cafbb9 100644 (file)
--- a/src/daComposant/daAlgorithms/ExtendedKalmanFilter.py
+++ b/src/daComposant/daAlgorithms/ExtendedKalmanFilter.py
@@ -1,6 +1,6 @@
-#-*-coding:iso-8859-1-*-
+# -*- coding: utf-8 -*-
 #
-# Copyright (C) 2008-2017 EDF R&D
+# Copyright (C) 2008-2018 EDF R&D
 #
 # This library is free software; you can redistribute it and/or
 # modify it under the terms of the GNU Lesser General Public
@@ -46,27 +46,31 @@ class ElementaryAlgorithm(BasicObjects.Algorithm):
             name     = "StoreInternalVariables",
             default  = False,
             typecast = bool,
-            message  = "Stockage des variables internes ou intermédiaires du calcul",
+            message  = "Stockage des variables internes ou intermédiaires du calcul",
             )
         self.defineRequiredParameter(
             name     = "StoreSupplementaryCalculations",
             default  = [],
             typecast = tuple,
-            message  = "Liste de calculs supplémentaires à stocker et/ou effectuer",
+            message  = "Liste de calculs supplémentaires à stocker et/ou effectuer",
             listval  = ["APosterioriCorrelations", "APosterioriCovariance", "APosterioriStandardDeviations", "APosterioriVariances", "BMA", "CurrentState", "CostFunctionJ", "CostFunctionJb", "CostFunctionJo", "Innovation"]
             )
         self.defineRequiredParameter( # Pas de type
             name     = "Bounds",
             message  = "Liste des valeurs de bornes",
             )
+        self.requireInputArguments(
+            mandatory= ("Xb", "Y", "HO", "R", "B" ),
+            optional = ("U", "EM", "CM", "Q"),
+            )
 
     def run(self, Xb=None, Y=None, U=None, HO=None, EM=None, CM=None, R=None, B=None, Q=None, Parameters=None):
-        self._pre_run(Parameters)
+        self._pre_run(Parameters, Xb, Y, R, B, Q)
         #
         if self._parameters["EstimationOf"] == "Parameters":
             self._parameters["StoreInternalVariables"] = True
         #
-        # Opérateurs
+        # Opérateurs
         # ----------
         if B is None:
             raise ValueError("Background error covariance matrix has to be properly defined!")
@@ -90,7 +94,7 @@ class ElementaryAlgorithm(BasicObjects.Algorithm):
         else:
             duration = 2
         #
-        # Précalcul des inversions de B et R
+        # Précalcul des inversions de B et R
         # ----------------------------------
         if self._parameters["StoreInternalVariables"]:
             BI = B.getI()