# -*- 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
# 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
# ==============================================================================
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",
# 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,
# ==============================================================================
if __name__ == "__main__":
- print('\n AUTODIAGNOSTIC \n')
+ print('\n AUTODIAGNOSTIC\n')