#'
#'@title Plot residuals from size frequency fits
#'
#' @description Plot Pearson's residuals or negative log-likelihood components
#' from size frequency fits.
#'
#' @param fits - list of fits
#' @param mc - model configuration list
#' @param plotPearsons - flag (T/F) to plot Pearson's residuals (T) or NLLs (F)
#' @param label - plot label
#'
#' @export
#'
plotZScoresForSizeFreqs<-function(fits,
mc,
plotPearsons=TRUE,
sxs=c(mc$SXs,"ALL_SEX"),
mss=c(mc$MSs,"ALL_MATURITY"),
scs=c(mc$SCs,"ALL_SHELL_CONDITION"),
label=""){
n<-length(fits);
yrs<-min(as.numeric(names(fits)),na.rm=TRUE):max(as.numeric(names(fits)),na.rm=TRUE)
zbs<-as.vector(mc$zBs);
dms<-c(length(sxs),length(mss),length(scs),length(yrs),length(zbs));
dmnames<-list(sx=sxs,ms=mss,sc=scs,yr=yrs,zb=zbs);
rAtZ<-array(0,dms,dmnames);
yrsp<-names(fits);
for (i in 1:(n-1)){
fit<-fits[[i]];
x<-fit$sx;
m<-fit$ms;
s<-fit$sc;
y<-yrsp[i];
if (plotPearsons){
pt<-"Pearson's residuals";
rAtZ[x,m,s,y,]<-fit$fit$zscrs;
} else {
rAtZ[x,m,s,y,]<-fit$fit$nlls;
pt<-"nll's";
}
}
for (x in sxs){
for (m in mss){
for (s in scs){
rAtZp<-t(as.matrix(rAtZ[x,m,s,,]));
if (sum(abs(rAtZp),na.rm=TRUE)>0){
sbt<-vector(mode="character",length=3);
if (substr(x,1,3)!="ANY") {sbt[1]<-x;}
if (substr(m,1,3)!="ANY") {sbt[2]<-m;}
if (substr(s,1,3)!="ANY") {sbt[3]<-s;}
sbtp<-paste(sbt[sbt!=""],collapse=", ");
plotCompsAsCircles(rAtZp,yrs,zbs,maxRadius=0.6,
main=label,subtitle=sbtp,
transparency=0.6,xlab="year",ylab="size (mm CW)");
mtext(pt,side=1,adj=0.01,outer=TRUE,line=-1);
}
}
}
}
}
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