ProxiesAttractor.Rd

% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/CST_ProxiesAttractor.R
\name{ProxiesAttractor}
\alias{ProxiesAttractor}
\title{Computing two dinamical proxies of the attractor.}
\usage{
ProxiesAttractor(data, quanti, ncores = NULL)
}
\arguments{
\item{data}{a multidimensional array with named dimensions to create the attractor. It requires a temporal dimension named 'time' and spatial dimensions called 'lat' and 'lon', or 'latitude' and 'longitude' or 'grid'.}

\item{quanti}{a number lower than 1 indicating the quantile to perform the computation of local dimension and theta}

\item{ncores}{The number of cores to use in parallel computation.}
}
\value{
dim and theta
}
\description{
This function computes two dinamical proxies of the attractor: 
The local dimension (d) and the inverse of the persistence (theta). 
These two parameters will be used as a condition for the computation of dynamical 
scores to measure predictability and to compute bias correction conditioned  by
the dynamics with the function DynBiasCorrection.  
Funtion based on the matlab code (davide.faranda@lsce.ipsl.fr) used in:
}
\examples{
# Example 1: Computing the attractor using simple data
# Creating an example of matrix data(time,grids):
mat <- array(rnorm(36 * 40), c(time = 36, grid = 40)) 
qm <- 0.90 # imposing a threshold
Attractor <- ProxiesAttractor(data = mat, quanti = qm)
# to plot the result
time = c(1:length(Attractor$theta))
layout(matrix(c(1, 3, 2, 3), 2, 2))
plot(time, Attractor$dim, xlab = 'time', ylab = 'd',
    main = 'local dimension', type = 'l')
plot(time, Attractor$theta, xlab = 'time', ylab = 'theta', main = 'theta') 
plot(Attractor$dim, Attractor$theta, col = 'blue', 
    main = "Proxies of the Attractor",
    xlab = "local dimension", ylab = "theta", lwd = 8, 'p')

}
\references{
Faranda, D., Alvarez-Castro, M.C., Messori, G., Rodriguez, D., and Yiou, P. (2019). 
The hammam effect or how a warm ocean enhances large scale atmospheric predictability.
Nature Communications, 10(1), 1316. DOI = https://doi.org/10.1038/s41467-019-09305-8 "

Faranda, D., Gabriele Messori and Pascal Yiou. (2017).
Dynamical proxies of North Atlantic predictability and extremes. 
Scientific Reports, 7-41278, 2017.
}
\author{
Carmen Alvarez-Castro, \email{carmen.alvarez-castro@cmcc.it}

Maria M. Chaves-Montero, \email{mdm.chaves-montero@cmcc.it}

Veronica Torralba, \email{veronica.torralba@cmcc.it}

Davide Faranda, \email{davide.faranda@lsce.ipsl.fr}
}