# readprm.R (filter parameters)
#
#readprm <- function(){
# Notes:
# loc_distype:
# - 'earth' assumes lat lon input coordinates for grid and observation positions
# then uses great circle distances fr localisation. Still $ll (localisation distance)
# has to be input in [m]
prm <- list()
prm$method <- rep('pMKF') # DA method 'oloop' for no assimilation ['pMFK','pIKF','FETKF','IETKF']
prm$maxiter <- 3 # maximum number of iterations for nonlinear assimilation
prm$ifrac <- 1 # this fraction [1 <= ifrac <= nfrac]
prm$loc_boo <- TRUE # whether to conduct localization 0 or 1 [apply to all elements in the augmented state vector]
prm$loc_method <- 'LA' # localization method. 'CF' (covariance filtering), or 'LA' (local analysis)
prm$loc_function <- 'Gaspari_Cohn' # tag for the localisation function (calc_loccoeffs.m)
prm$loc_distype <- 'earth' # '2D' for Euclidean, or 'SG' for along network distances [apply to all elements in the augmented state vector]
prm$rotate <- FALSE # 0 = do not rotate. 1 = rotate. The code has to prepared to set prm.rotate each some assimilation steps
prm$rotate_ampl <- 1 # always 1. Code not prepared for other values
prm$sdfac <- 0.001 # OPT, used only for parameter-space methods. Scaler of standard deviations for parameter perturbation.
#return(prm)
#}
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