#' Histogram of the ESS values
#'
#' Plots the histogram of the ESS values for the continuous parameters
#'
#' @importFrom grDevices dev.off pdf
#' @importFrom graphics abline hist layout legend lines par points polygon rect title
#'
#' @param x A list of convenience.diag type
#' @param per_run If the plot should combine all runs or plot each run separately. Default value is FALSE
#' @param precision The precision of the mean estimates. Default is 0.01
#' @param breaks The number of bins to determine the intervals of the histogram
#' @param fill_color The color to fill the histogram bars
#' @param filename The name of the file to save the plot
#' @param xlab Defines the label for the x-axis. To remove the label set to NA. Default = NULL
#' @param ylab Defines the label for the y-axis. To remove the label set to NA. Default = NULL
#' @param title Defines the title of the plot. To remove the title set to NA. Default = NULL
#' @param ... (various) Additional arguments passed to plot().
#'
#' @return Histogram
#'
#' @export
plotEssContinuous <- function(x, per_run = FALSE, precision = 0.01, breaks = NULL,fill_color = NULL, filename = NULL, xlab = NULL, ylab = NULL, title = NULL, ...){
# Calculates min ESS according to the std error of the mean
minESS <- function(per){
return((1/(per*4))^2)
}
col_threshold <- "gray69"
if( is.null(fill_color) ){
fill_color <- "cadetblue4"
}
if( !(is.null(filename)) ){
pdf(file = filename, width = 4.5, height = 4.5)
}
minimumESS <- minESS(precision)
ESS_values <- vector()
if(per_run == TRUE){
n_runs <- ncol(x$continuous_parameters$ess)
par(mfrow = c(n_runs/2,n_runs/2), oma = c(1.5,1.5,1.5,0) + 0.1, mar = c(2,2,2.3,2))
layout(matrix(c(1:n_runs), nrow=n_runs/2, ncol = n_runs/2, byrow=TRUE))
for (i in 1:n_runs) {
ESS_values <- x$continuous_parameters$ess[,i]
ESS_values <- ESS_values[!is.na(ESS_values)]
if(is.null(breaks)){
breaks <- seq(0, (max(minimumESS, ESS_values))+50, 25)
}
y_topLim <- max(hist(ESS_values, plot = FALSE)$counts)
x_topLim <- max(minimumESS,ESS_values) + (max(minimumESS, ESS_values))/10
plot <- plot(NA,
xlab = NA,
ylab = NA,
main = colnames(x$continuous_parameters$ess)[i],
xlim = c(0, x_topLim ),
ylim = c(0, y_topLim+1),
las=1,
bty="l")
plot <- rect(xleft = minimumESS, ybottom = 0, xright = x_topLim, ytop = y_topLim+1, border = NA, col = "gray89")
plot <- lines(x = c(minimumESS,minimumESS),y=c(0,y_topLim+1), col = col_threshold, lwd= 2, lty=2)
plot <- hist(ESS_values,
xlab = NA,
ylab = NA,
xlim = c(0, x_topLim ),
ylim = c(0, y_topLim+1),
border = F,
col = fill_color,
add=T,
...)
}
if( is.null(xlab)) xlab <- "Effective Sample Size" else xlab <- xlab
if( is.null(ylab)) ylab <- "Counts" else ylab <- ylab
if( is.null(title)) title <- "Effective Sample Size for continuous parameters per run" else title <- title
title(main = title, xlab = xlab, ylab = ylab, outer = TRUE, line = 0.5, cex.main = 0.9)
} else {
for (i in 1:ncol(x$continuous_parameters$ess)) {
ESS_values <- c(ESS_values, x$continuous_parameters$ess[,i])
ESS_values <- ESS_values[!is.na(ESS_values)]
}
if(is.null(breaks)){
breaks <- seq(0, (max(minimumESS, ESS_values))+50, 25)
}
y_topLim <- max(hist(ESS_values, breaks = 10, plot = FALSE)$counts)
x_topLim <- max(minimumESS,ESS_values) + (max(minimumESS, ESS_values))/10
par(mar = c(4.1, 3.9, 2.1, 1.0))
if( is.null(xlab)) xlab <- "Effective Sample Size" else xlab <- xlab
if( is.null(ylab)) ylab <- "Counts" else ylab <- ylab
if( is.null(title)) title <- "Effective Sample Size for continuous parameters" else title <- title
plot <- plot(NA,
xlab = xlab,
ylab = ylab,
main = title,
cex.main = 0.9,
xlim = c(0, x_topLim ),
ylim = c(0, y_topLim+1),
las=1,
bty="l")
plot <- rect(xleft = minimumESS, ybottom = 0, xright = x_topLim, ytop = y_topLim+1, border = NA, col = "gray89")
plot <- lines(x = c(minimumESS,minimumESS),y=c(0,y_topLim+1), col = col_threshold, lwd= 2, lty=2)
plot <- hist( ESS_values,
breaks = breaks,
xlim = c(0, x_topLim ),
ylim = c(0, y_topLim+1),
border = F,
col = fill_color,
add=T,
...)
}
if( !(is.null(filename)) ){
dev.off()
}
}
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