SailoR.Table {SailoR}

Summary of indices calculated for the Sailor diagrams

Description

This function reads the output from SailoR.Indices() and creates a summary data frame of the indices calculated for the Sailor diagram. This can easily be converted to a LaTeX or other formats with external packages ('xtable', for instance).

Usage

SailoR.Table(UV, round_digits = 2)

Arguments

UV

a list containing the output obtained directly from SailoR.Indices() function.

round_digits

number of decimals to be kept in the summary table.

Value

The result is a data frame with the information from the SailoR.Indices() function in tabular format. Particularly, the indices stated in the table are the following ones:

modelName

the names of the models datasets.

sdUx

standard deviation of zonal component (U).

sdUy

standard deviation of meridional component (U).

sdVx

standard deviation of zonal component (V).

sdVy

standard deviation of meridional component (V).

Sigmax

a scalar representing the semi-major axis of the ellipse (standard deviation of PC1).

Sigmay

a scalar representing the semi-minor axis of the ellipse (standard deviation of PC2).

thetau

angle of EOF1 (U) with zonal axis.

thetav

angle of EOF1 (V) with meridional axis.

thetavu

rotation angle from U EOFs to V EOFs.

R2vec

vector correlation squared in 2D as defined by Breaker, Gemmill and Crossby (1994).

biasMag

magnitude of the bias vector.

RMSE

root mean square error between U and V.

Eccentricity

eccentricity of the ellipses from the reference and models dataset.

congruenceEOF1

congruence coefficients (absolute value) for EOF1.

Examples

#--------------------------------------------------------
# Example 1
#--------------------------------------------------------
# Load the ocean current data 
data("Current")
  
# Calculate the statistics
ref<-Current[["ref"]]
mod<-Current[["mod"]]
UV <- SailoR.Indices(ref,mod)

# Obtain the summary of the results
SailoR.Table(UV)

#--------------------------------------------------------
# Example 2: Table 2 from Sáenz et al. (2020)
#--------------------------------------------------------
# Load Synthetic data 
data(Synthetic)

ref<-Synthetic[["ref"]]
mod<-Synthetic[["mod"]]

# Calculate the statistics
UVtable=SailoR.Table(UV,round_digits = 4)
TotVar<-c((UVtable$sdUx^2+UVtable$sdUy^2)[1],
          (UVtable$sdVx^2+UVtable$sdVy^2)[-1])
TotSigma<-UVtable$Sigmax^2+UVtable$Sigmay^2
UVtable<-cbind(UVtable[,1],TotVar,TotSigma,UVtable[,8:15])

UVtable<-round(UVtable[,-1],2)

#If you want to print it as a LaTeX table:
#library(xtable)
#oInfo<-xtable(UVtable)
#print(oInfo,type="latex",file="table.tex")