# -*- coding: utf-8 -*-
#
-# Copyright (C) 2008-2020 EDF R&D
+# Copyright (C) 2008-2021 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
def __init__(self):
BasicObjects.Algorithm.__init__(self, "ENSEMBLEKALMANFILTER")
self.defineRequiredParameter(
- name = "Minimizer",
- default = "StochasticEnKF",
+ name = "Variant",
+ default = "EnKF",
typecast = str,
- message = "Minimiseur utilisé",
- listval = ["StochasticEnKF", "DeterministicEnKF", "ETKF"],
+ message = "Variant ou formulation de la méthode",
+ listval = [
+ "EnKF",
+ "ETKF",
+ "ETKF-N",
+ "MLEF",
+ "IEnKF",
+ ],
+ listadv = [
+ "StochasticEnKF",
+ "EnKF-05",
+ "EnKF-16",
+ "ETKF-KFF",
+ "ETKF-VAR",
+ "ETKF-N-11",
+ "ETKF-N-15",
+ "ETKF-N-16",
+ "MLEF-T",
+ "MLEF-B",
+ "IEnKF-T",
+ "IEnKF-B",
+ "IEKF",
+ ],
)
self.defineRequiredParameter(
name = "NumberOfMembers",
default = 100,
typecast = int,
message = "Nombre de membres dans l'ensemble",
- minval = -1,
+ minval = 2,
)
self.defineRequiredParameter(
name = "EstimationOf",
message = "Estimation d'etat ou de parametres",
listval = ["State", "Parameters"],
)
+ self.defineRequiredParameter(
+ name = "InflationType",
+ default = "MultiplicativeOnAnalysisCovariance",
+ typecast = str,
+ message = "Méthode d'inflation d'ensemble",
+ listval = [
+ "MultiplicativeOnAnalysisCovariance",
+ "MultiplicativeOnBackgroundCovariance",
+ "MultiplicativeOnAnalysisAnomalies",
+ "MultiplicativeOnBackgroundAnomalies",
+ "AdditiveOnAnalysisCovariance",
+ "AdditiveOnBackgroundCovariance",
+ "HybridOnBackgroundCovariance",
+ ],
+ )
+ self.defineRequiredParameter(
+ name = "InflationFactor",
+ default = 1.,
+ typecast = float,
+ message = "Facteur d'inflation",
+ minval = 0.,
+ )
+ self.defineRequiredParameter(
+ name = "LocalizationType",
+ default = "SchurLocalization",
+ typecast = str,
+ message = "Méthode d'inflation d'ensemble",
+ listval = [
+ "SchurLocalization",
+ ],
+ listadv = [
+ "CovarianceLocalization",
+ "DomainLocalization",
+ "GaspariCohnLocalization",
+ ],
+ )
+ self.defineRequiredParameter(
+ name = "LocalizationFactor",
+ default = 1.,
+ typecast = float,
+ message = "Facteur de localisation",
+ minval = 0.,
+ )
+ self.defineRequiredParameter( # Pas de type
+ name = "LocalizationMatrix",
+ message = "Matrice de localisation ou de distances",
+ )
self.defineRequiredParameter(
name = "SetSeed",
typecast = numpy.random.seed,
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, Xb, Y, U, HO, EM, CM, R, B, Q)
#
- if self._parameters["Minimizer"] == "StochasticEnKF":
- NumericObjects.senkf(self, Xb, Y, U, HO, EM, CM, R, B, Q)
- elif self._parameters["Minimizer"] in ["DeterministicEnKF", "ETKF"]:
- NumericObjects.etkf(self, Xb, Y, U, HO, EM, CM, R, B, Q)
+ #--------------------------
+ # Default EnKF = EnKF-16 = StochasticEnKF
+ if self._parameters["Variant"] == "EnKF-05":
+ NumericObjects.senkf(self, Xb, Y, U, HO, EM, CM, R, B, Q, VariantM="KalmanFilterFormula05")
+ #
+ elif self._parameters["Variant"] in ["EnKF-16", "StochasticEnKF", "EnKF"]:
+ NumericObjects.senkf(self, Xb, Y, U, HO, EM, CM, R, B, Q, VariantM="KalmanFilterFormula16")
+ #
+ #--------------------------
+ # Default ETKF = ETKF-KFF
+ elif self._parameters["Variant"] in ["ETKF-KFF", "ETKF"]:
+ NumericObjects.etkf(self, Xb, Y, U, HO, EM, CM, R, B, Q, VariantM="KalmanFilterFormula")
+ #
+ elif self._parameters["Variant"] == "ETKF-VAR":
+ NumericObjects.etkf(self, Xb, Y, U, HO, EM, CM, R, B, Q, VariantM="Variational")
+ #
+ #--------------------------
+ # Default ETKF-N = ETKF-N-16
+ elif self._parameters["Variant"] == "ETKF-N-11":
+ NumericObjects.etkf(self, Xb, Y, U, HO, EM, CM, R, B, Q, VariantM="FiniteSize11")
+ #
+ elif self._parameters["Variant"] == "ETKF-N-15":
+ NumericObjects.etkf(self, Xb, Y, U, HO, EM, CM, R, B, Q, VariantM="FiniteSize15")
+ #
+ elif self._parameters["Variant"] in ["ETKF-N-16", "ETKF-N"]:
+ NumericObjects.etkf(self, Xb, Y, U, HO, EM, CM, R, B, Q, VariantM="FiniteSize16")
+ #
+ #--------------------------
+ # Default MLEF = MLEF-T
+ elif self._parameters["Variant"] in ["MLEF-T", "MLEF"]:
+ NumericObjects.mlef(self, Xb, Y, U, HO, EM, CM, R, B, Q, BnotT=False)
+ #
+ elif self._parameters["Variant"] == "MLEF-B":
+ NumericObjects.mlef(self, Xb, Y, U, HO, EM, CM, R, B, Q, BnotT=True)
+ #
+ #--------------------------
+ # Default IEnKF = IEnKF-T
+ elif self._parameters["Variant"] in ["IEnKF-T", "IEnKF"]:
+ NumericObjects.ienkf(self, Xb, Y, U, HO, EM, CM, R, B, Q, BnotT=False)
+ #
+ elif self._parameters["Variant"] in ["IEnKF-B", "IEKF"]:
+ NumericObjects.ienkf(self, Xb, Y, U, HO, EM, CM, R, B, Q, BnotT=True)
+ #
+ #--------------------------
else:
- raise ValueError("Error in Minimizer name: %s"%self._parameters["Minimizer"])
+ raise ValueError("Error in Variant name: %s"%self._parameters["Variant"])
#
self._post_run(HO)
return 0