Localizers
EnsembleKalmanProcesses.Localizers.Localizer
— TypeLocalizer{LM <: LocalizationMethod, T}
Structure that defines a localize
function, based on a localization method.
Fields
localize::Function
Localizing function of the form:
cov -> kernel .* cov
Constructors
Localizer(localization, p, d, J)
Localizer(localization, p, d, J, T)
defined at /home/runner/work/EnsembleKalmanProcesses.jl/EnsembleKalmanProcesses.jl/src/Localizers.jl:122
.
Localizer(localization, p, d, J)
Localizer(localization, p, d, J, T)
defined at /home/runner/work/EnsembleKalmanProcesses.jl/EnsembleKalmanProcesses.jl/src/Localizers.jl:128
.
Localizer(localization, p, d, J)
Localizer(localization, p, d, J, T)
defined at /home/runner/work/EnsembleKalmanProcesses.jl/EnsembleKalmanProcesses.jl/src/Localizers.jl:134
.
Localizer(localization, p, d, J)
Localizer(localization, p, d, J, T)
defined at /home/runner/work/EnsembleKalmanProcesses.jl/EnsembleKalmanProcesses.jl/src/Localizers.jl:179
.
Localizer(localization, p, d, J)
Localizer(localization, p, d, J, T)
defined at /home/runner/work/EnsembleKalmanProcesses.jl/EnsembleKalmanProcesses.jl/src/Localizers.jl:199
.
Localizer(localization, p, d, J)
Localizer(localization, p, d, J, T)
defined at /home/runner/work/EnsembleKalmanProcesses.jl/EnsembleKalmanProcesses.jl/src/Localizers.jl:238
.
EnsembleKalmanProcesses.Localizers.RBF
— TypeRBF{FT <: Real} <: LocalizationMethod
Radial basis function localization method. Covariance terms $C_{i,j}$ are damped through multiplication with a centered Gaussian with standardized deviation $d(i,j)= \vert i-j \vert / l$.
Fields
lengthscale::Real
Length scale defining the RBF kernel
EnsembleKalmanProcesses.Localizers.BernoulliDropout
— TypeBernoulliDropout{FT <: Real} <: LocalizationMethod
Localization method that drops cross-covariance terms with probability $1-p$, retaining a Hermitian structure.
Fields
prob::Real
Probability of keeping a given cross-covariance term
EnsembleKalmanProcesses.Localizers.SEC
— TypeSEC{FT <: Real} <: LocalizationMethod
Sampling error correction that shrinks correlations by a factor of $\vert r \vert ^\alpha$, as per Lee (2021). Sparsity of the resulting correlations can be imposed through the parameter r_0
.
Lee, Y. (2021). Sampling error correction in ensemble Kalman inversion. arXiv:2105.11341 [cs, math]. http://arxiv.org/abs/2105.11341
Fields
α::Real
Controls degree of sampling error correction
r_0::Real
Cutoff correlation
EnsembleKalmanProcesses.Localizers.SECFisher
— TypeSECFisher <: LocalizationMethod
Sampling error correction for EKI, as per Lee (2021), but using the method from Flowerdew (2015) based on the Fisher transformation. Correlations are shrinked by a factor determined by the sample correlation and the ensemble size.
Flowerdew, J. (2015). Towards a theory of optimal localisation. Tellus A: Dynamic Meteorology and Oceanography, 67(1), 25257. https://doi.org/10.3402/tellusa.v67.25257
Lee, Y. (2021). Sampling error correction in ensemble Kalman inversion. arXiv:2105.11341 [cs, math]. http://arxiv.org/abs/2105.11341
EnsembleKalmanProcesses.Localizers.Delta
— TypeDirac delta localization method, with an identity matrix as the kernel.
EnsembleKalmanProcesses.Localizers.NoLocalization
— TypeIdempotent localization method.