#' Plot histogram of time-varying k
#'
#' @export
#'
plot_histogram_k <- function(data, report, file_name = "REs_b", delta_t = "weeks")
{
if (delta_t == "weeks") adj <- 52.15
if (delta_t == "months") adj <- 12
if (delta_t == "years") adj <- 1
REs_b <- exp(report$par.random[names(report$par.random) %in% "ln_bdev"])
Sex <- data$Sex
d <- data.frame(Sex, REs_b)
dat <- melt(d, id.vars = "Sex")
dat$Sex[dat$Sex == 1] <- "Females"
dat$Sex[dat$Sex == 2] <- "Males"
mu_b <- exp(report$par.fixed[names(report$par.fixed) %in% "ln_bmean"])
dat$mu_b[dat$Sex == "Females"] <- mu_b[1]
dat$mu_b[dat$Sex == "Males"] <- mu_b[2]
# Make k annual rather than whatever is being used
dat$value <- dat$value * dat$mu_b * adj
dat$mu_b <- dat$mu_b * adj
p <- ggplot(data = dat, aes(x = value)) +
geom_histogram(aes(y = ..density..), colour = "black", fill = "grey") +
geom_vline(aes(xintercept = mu_b), size = 0.75, colour = "red") +
facet_grid(~ Sex) +
xlab("\nk") + ylab("Density\n") +
plot_theme() +
scale_colour_manual(values = plot_palette)
png(paste(file_name, ".png", sep = ""), width = 8, height = 4, units = "in", res = 400)
print(p)
dev.off()
}
# Plot histogram of REs
#png("REs.png", width=5, height=5, units="in", res=300)
#par(mfrow=c(2,2))
#xlim <- range(Report$value[names(Report$value) %in% "bmean"][1]*exp(REs_b))
#hist((Report$value[names(Report$value) %in% "bmean"][1]*exp(REs_b))[ATR_mod$Sex==1], xlab="b", main="Females", las = 1, xlim = xlim, col = "grey")
#abline(v=Report$value[names(Report$value) %in% "bmean"][1], col=2, lwd=2, lty = 2)
#box()
#hist((Report$value[names(Report$value) %in% "bmean"][2]*exp(REs_b))[ATR_mod$Sex==2], xlab="b", main="Males", las = 1, xlim = xlim, col = "grey")
#abline(v=Report$value[names(Report$value) %in% "bmean"][2], col=2, lwd=2, lty = 2)
#box()
#xlim <- range(REs_z1, REs_z2)
#hist(REs_z1, xlab="z1", main = "", las = 1, col = "grey", xlim = xlim)
#box()
#hist(REs_z2, xlab="z2", main = "", las = 1, col = "grey", xlim = xlim)
#box()
#dev.off()
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