if (params$tabs) { cat('### Historical MPA & Spatial Targeting {.tabset .tabset-fade .tabset-pills}' ) } else { cat('### Historical MPA & Spatial Targeting') } dd <- dim(params$Pars$Stock$M_ageArray) nsim <- dd[1] maxage <- dd[2] nsamp <- length(params$its)
CURRENTLY NOT IMPLEMENTED !
# if (all(is.na(Pars$MPA)) | sum(Pars$MPA) == 0) { # Pars$MPA <- matrix(NA, nrow=2, ncol=3) # Pars$MPA[,1] <- c(1, nyears) # Pars$MPA[,2:3] <- 1 # } # # # historical spatial closures have been specified # sim <- params$its[1] # nareas <- dim(Pars$mov)[3] # ncol(Pars$MPA)-1 # MPA <- matrix(1, nyears+proyears, ncol=nareas) # yrindex <- Pars$MPA[,1] # if (max(yrindex)>nyears) stop("Invalid year index for spatial closures: must be <= nyears") # if (min(yrindex)<1) stop("Invalid year index for spatial closures: must be > 1") # for (xx in seq_along(yrindex)) { # MPA[yrindex[xx]:nrow(MPA),] <- matrix(Pars$MPA[xx, 2:ncol(Pars$MPA)], # nrow=length(yrindex[xx]:nrow(MPA)),ncol=nareas, byrow = TRUE) # } # x <- 1:(nyears+proyears) # nyrs <- length(x) # op <- par(mfrow=c(1,1), mar=c(3,3,0,0), oma=c(0,0,0,0), no.readonly = TRUE) # on.exit(par(op)) # # area_sizes <- Pars$Asize[sim,] # names(area_sizes) <- NULL # plot(c(1, nyears+proyears), c(0,sum(area_sizes)), type="n", bty="n", xlab="", ylab="", axes=FALSE) # origin <- cumsum(c(0, area_sizes)) # seq(0, by=1, length.out = nareas) # # for (aa in 1:nareas) { # if (aa ==1) { # df <- data.frame(Years=x, y1=0, y2=area_sizes[aa] * MPA[,aa]) # } else { # df <- data.frame(Years=x, y1=sum(area_sizes[1:(aa-1)]), y2=sum(area_sizes[1:(aa-1)])+(area_sizes[aa] * MPA[,aa])) # } # polygon(x=c(df$Years, rev(df$Years)), y=c(df$y1, rev(df$y2)), # col='lightgray', border = TRUE) # } # # if (Pars$CurrentYr < 1000) years <- (Pars$CurrentYr - nyears+1) : (Pars$CurrentYr+proyears) -Pars$CurrentYr # if (Pars$CurrentYr > 1000) years <- (Pars$CurrentYr - nyears+1) : (Pars$CurrentYr+proyears) # # xp <- seq(from=min(x), to=max(x), by=5) # ind <- match(xp, x) # # axis(side=1, at=x[ind], labels=years[ind]) # mtext(side=1, "Years", line=2, xpd=NA, cex=1.25) # # axis(side=2, at=origin[1:(length(origin)-1)] + 0.5 * area_sizes, labels=1:nareas, las=1, col = "white", tcl = 0) # # mtext(side=2, "Areas", line=2, xpd=NA, cex=1.25, las=3) # abline(v=nyears, lty=2, col="darkgray") # # mtext('Fraction open to fishing (grey)', side=3, line=2)
Histograms of r nsim
simulations of spatial targeting parameter (Spat_targ
), with vertical colored lines indicating r nsamp
randomly drawn values:
MSEtool:::plot.MPA(params$Pars, nsamp=nsamp, plotPars=params$plotPars, plot.num=1)
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