### CYSTIRUN METHODS
print.cystiRun <-
function(x, from = 200, to = NA, ...) {
if (is.na(to)) to <- nrow(x$out)
p <- colMeans(x$out[seq(from, to), ])
cat("PC: ", round(p[1], 3),
"| Pr(H):", round(p[2], 3), "\n")
cat("PCI:", round(p[4], 3), "\n")
cat("HT: ", round(p[6], 4),
"| HT(inf):", round(p[7], 4),
", HT(chl):", round(p[8], 4),
", HT(adl):", round(p[9], 4), "\n")
cat("E: ", round(p[10], 4), "\n")
}
plot.cystiRun <-
function(x, y = NULL, show = c("PC", "PR", "HT", "EN"),
start = 0, from = 1, to = NA, ...) {
## define census labels and groups
label <- c("PC", "P(H)", "P(L)", "PCI", "PR",
"HT", "HT(inf)", "HT(ch)", "HT(ad)", "EN")
group <- c(rep("pig", 5), rep("man", 5))
## select labels and groups to show
id_col <- match(show, label)
lab <- factor(label[id_col], levels = label[id_col])
grp <- factor(group[id_col], levels = unique(group[id_col]))
## define extraction points
if (is.na(to)) to <- nrow(x$out)
id_row <- seq(from, to)
## extract census data; force matrix
out <- as.matrix(x$out[id_row, id_col])
## define months
months <- seq(nrow(out)) - start
## create ggplot data.frame
df <- data.frame(p = c(out),
m = rep(months, times = ncol(out)),
lab = rep(lab, each = nrow(out)),
grp = rep(grp, each = nrow(out)))
## build plot function
ggplot(df, aes_string(x = "m", y = "p")) +
geom_line(aes(col = lab)) +
scale_colour_manual(values = seq(10)[id_col]) +
facet_grid(grp ~ ., scales = "free", as.table = FALSE) +
scale_x_continuous("month") +
scale_y_continuous("proportion") +
theme_bw()
}
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