X-Git-Url: http://git.salome-platform.org/gitweb/?a=blobdiff_plain;f=src%2FdaComposant%2FdaAlgorithms%2FQuantileRegression.py;h=4b0dd223528f1ad1c12dab21206bc9de2e779e0c;hb=67a9e7898a4e0455f469b63898f42e965da0b33e;hp=11cc832a5bcb8b2a2f271f2dd4220f609c4ebf85;hpb=953c9745b5a2e2b75fa34fbab7cf3383693b5a0e;p=modules%2Fadao.git

diff --git a/src/daComposant/daAlgorithms/QuantileRegression.py b/src/daComposant/daAlgorithms/QuantileRegression.py
index 11cc832..4b0dd22 100644
--- a/src/daComposant/daAlgorithms/QuantileRegression.py
+++ b/src/daComposant/daAlgorithms/QuantileRegression.py
@@ -1,6 +1,6 @@
 # -*- coding: utf-8 -*-
 #
-# Copyright (C) 2008-2018 EDF R&D
+# Copyright (C) 2008-2019 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
@@ -21,7 +21,7 @@
 # Author: Jean-Philippe Argaud, jean-philippe.argaud@edf.fr, EDF R&D
 
 import logging
-from daCore import BasicObjects
+from daCore import BasicObjects, NumericObjects
 import numpy
 
 # ==============================================================================
@@ -67,7 +67,20 @@ class ElementaryAlgorithm(BasicObjects.Algorithm):
             default  = [],
             typecast = tuple,
             message  = "Liste de calculs supplémentaires à stocker et/ou effectuer",
-            listval  = ["BMA", "OMA", "OMB", "CurrentState", "CostFunctionJ", "CostFunctionJb", "CostFunctionJo", "Innovation", "SimulatedObservationAtBackground", "SimulatedObservationAtCurrentState", "SimulatedObservationAtOptimum"]
+            listval  = [
+                "Analysis",
+                "BMA",
+                "CostFunctionJ",
+                "CostFunctionJb",
+                "CostFunctionJo",
+                "CurrentState",
+                "Innovation",
+                "OMA",
+                "OMB",
+                "SimulatedObservationAtBackground",
+                "SimulatedObservationAtCurrentState",
+                "SimulatedObservationAtOptimum",
+                ]
             )
         self.defineRequiredParameter( # Pas de type
             name     = "Bounds",
@@ -131,8 +144,7 @@ class ElementaryAlgorithm(BasicObjects.Algorithm):
         # Minimisation de la fonctionnelle
         # --------------------------------
         if self._parameters["Minimizer"] == "MMQR":
-            import mmqr
-            Minimum, J_optimal, Informations = mmqr.mmqr(
+            Minimum, J_optimal, Informations = NumericObjects.mmqr(
                 func        = CostFunction,
                 x0          = Xini,
                 fprime      = GradientOfCostFunction,
@@ -177,4 +189,4 @@ class ElementaryAlgorithm(BasicObjects.Algorithm):
 
 # ==============================================================================
 if __name__ == "__main__":
-    print('\n AUTODIAGNOSTIC \n')
+    print('\n AUTODIAGNOSTIC\n')