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### This file contains the function for fitness distirbution plot.
### Plot the posterior distribution by each mixture component with
### sorted cluster.
plotfd <- function(X, pcobj, merge = TRUE,
main = NULL, xlab = NULL, ylab = NULL, ...){
N <- pcobj$N
K <- pcobj$K
post.class <- sort(pcobj$class.id)
post <- pcobj$Z.normalized[order(pcobj$class.id),]
for(k in 1:K){
id <- which(post.class == k)
id.new <- order(post[id, k], decreasing = TRUE)
post[id,] <- post[id[id.new],]
}
xlim <- c(1, N)
ylim <- c(0, 1)
if(is.null(main)) main <- "Distribution Plot"
if(is.null(xlab)) xlab <- "Sequence (sorted)"
if(is.null(ylab)) ylab <- "Posterior"
color <- .Color[1:K %% length(.Color) + 1]
x <- 1:N
if(merge){
if(K == 1){
plot(NULL, NULL, xlim = xlim, ylim = ylim,
main = main, xlab = xlab, ylab = "K = 1")
y <- post[, 1]
lines(list(x = x, y = y), col = color[1])
} else{
plot(NULL, NULL, xlim = xlim, ylim = ylim,
main = main, xlab = xlab, ylab = ylab)
for(k in 1:K){
lines(list(x = x, y = post[, k]), col = color[k], lwd = 3, lty = k)
}
}
} else{
v <- cumsum(pcobj$n.class)[1:(K-1)] + 0.5
if(K == 1){
plot(NULL, NULL, xlim = xlim, ylim = ylim,
main = main, xlab = xlab, ylab = "K = 1")
y <- post[, 1]
lines(list(x = x, y = y), col = color[1])
abline(v = v, lty = 3)
} else{
par(mfrow = c(K, 1))
plot(NULL, NULL, xlim = xlim, ylim = ylim,
main = main, xlab = "", ylab = "K = 1", axes = FALSE)
lines(list(x = x, y = post[, 1]), col = color[1], lwd = 2)
axis(2)
abline(v = v, lty = 3)
for(k in 2:(K - 1)){
plot(NULL, NULL, xlim = xlim, ylim = ylim,
xlab = "", ylab = paste("K =", k), axes = FALSE)
lines(list(x = x, y = post[, k]), col = color[k], lwd = 2)
axis(2)
abline(v = v, lty = 3)
}
plot(NULL, NULL, xlim = xlim, ylim = ylim,
main = "", xlab = xlab, ylab = paste("K =", K), axes = FALSE)
lines(list(x = x, y = post[, K]), col = color[K], lwd = 2)
axis(1)
axis(2)
abline(v = v, lty = 3)
}
}
} # End of plotfd().
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