FLR4MFCL: R Functions for Taming MULTIFAN-CL

#FLR4MFCL - R4MFCL built with FLR classes
#Copyright (C) 2018  Rob Scott

################################################
##
## Regional contributions to spawning biomass plot
##
## rds 11/06/2017
##
## these functions have been moved to mi-wantem-luk 10/08/2023
##
################################################

# par <- read.MFCLPar("Q:\\skj\\2016\\assessment\\RefCase\\11.par")
# rep <- read.MFCLRep("Q:\\skj\\2016\\assessment\\RefCase\\plot-11.par.rep")
# contributions.plot(par, rep, Fmult=2, propn=F)
# par <- read.MFCLPar("/home/rob/MSE/skj/MSE_grid_2019/A0B0C0D0E0_fit/07.par")
# rep <- read.MFCLRep("/home/rob/MSE/skj/MSE_grid_2019/A0B0C0D0E0_fit/plot-07.par.rep")




# contributions <- function(par, rep, Fmult=0, propn=TRUE){
# 
#   nages   <- dimensions(par)['agecls']
#   ssns    <- dimensions(par)['seasons']
#   regions <- dimensions(par)['regions']
# 
#   # m <- c(aperm(m_at_age(rep), c(4,1,2,3,5,6)))
#   m <- m_at_age(rep)
#   # fec <- c(aperm(mat(par), c(4,1,2,3,5,6)))
#   fec <- mat(par)
#   f <- fm(rep)[,as.character(range(rep)['maxyear'])]
# 
#   # Calculate average recruitment by region and season for an appropriate period
#   recdist <- yearMeans(rec_region(rep))
#   # recdist <- yearMeans(trim(rec_region(rep), year=1982:2014))
#   # recdist <- region_pars(par)[1,]
# 
#   pop <- FLQuant(0, dimnames=list(age=1:nages, year="all", unit="unique", season=1:ssns, area=1:regions, iter=1:regions))
# 
#   # Seed the recruitment values
#   for(rr in 1:regions)
#     pop[1,,,,rr,rr] <- recdist[,,,,rr,]
# 
#   # Calculate popn numbers
#   for(ii in 1:regions)
#     for(qq in 1:ssns)
#       for(aa in 2:nages)
#         pop[aa,,,qq,ii] <- pop[aa-1,,,qq,ii] %*% diff_coffs_age_period(par)[,,aa,qq] * exp(-m[aa]-c(f[aa,,,qq,ii,]*Fmult))
# 
#   pop_ab <- seasonMeans(quantSums(sweep(pop, 1, waa(par)*fec, "*")))
# 
#   dat <- aperm(pop_ab, c(6,5,1,2,3,4))[,,1,1,1,1]
# }
#   
# contributionsPlot <- function(par, rep, Fmult=0, propn=TRUE, cols=NULL){
#   
#   dat <- contributions(par, rep, Fmult, propn){
#     
#   # Plotting stuff - using legacy code where possible
#   if(is.null(cols))
#     cols <- gray(seq(0,1,length.out=regions+2))[-c(1,regions)]
# 
#   # X11(2000, 1400)
#   layout(matrix(c(1,2),2,1,byrow=TRUE), c(35,20), c(20,5), TRUE)
#   par(mar=c(2.5,3,2,2))
# 
#   if(propn)
#     barplot(sweep(dat, 2, apply(dat, 2, sum), '/'), col=cols, names.arg= paste("Reg", 1:regions),las=1)
#   if(!propn)
#     barplot(dat, col=cols, names.arg= paste("Reg", 1:regions),las=1)
# 
#   mtext(side=2, "Proportion of biomass by source region", line=2.5)
#   a <- barplot(dat, col=rainbow(6), plot=FALSE)
# 
#   # Dummy plot to plot legend
#   par(mar=c(2,3,0,2))
#   plot(0,0, ylim=c(0,1), xlim=c(0,(max(a)+a[1]/2)), type="n", ylab="", xlab="", yaxt="n", xaxt="n", xpd=T, bty="n")
#   points(a-0.2, rep(1,length(a)), pch=15, cex=6, col=cols,xpd=T, bty="n")
# 
# }

# contributions.plot(par, rep, Fmult=0, propn=TRUE)