resPath <- "resData/DBNR/confidenceEnvelopes"
resPath <- R.utils::Arguments$getReadablePath(resPath)
figPath <- R.utils::Arguments$getReadablePath("fig/DBNR")
configs <- expand.grid(
grouped = groupeds,
setting = settings,
stringsAsFactors = FALSE)
grouped <- TRUE
setting <- "const"
for (grouped in unique(configs$grouped)) {
for (setting in unique (configs$setting)) {
filename <- sprintf("conf-env-alpha_grouped=%s_setting=%s.rds", grouped, setting)
pathname <- file.path(resPath, filename)
dat <- readRDS(pathname)
rm(pathname)
dim(dat)
names(dat)
oo <- "p.value"
sdat <- subset(dat, s == 100 & K1 == 8 & d > 0.5 & order == oo)
dim(sdat)
library("magrittr")
library("dplyr")
gdat <- sdat %>% group_by(idxs, method, d, barmu, alpha)
pdat <- gdat %>% summarise(value = mean(value))
library("ggplot2")
m1 <- unique(sdat$s)*unique(sdat$K1)*max(sdat$d)
xymax <- 4/3*m1
ff <- gsub("\\.rds$", ".pdf", filename)
pathname <- file.path(figPath, ff)
pdat <- subset(pdat, alpha %in% c(0.001, 0.01, 0.1, 0.25, 0.5))
pdat$alpha <- as.factor(pdat$alpha)
ggplot(pdat, aes(idxs, value, colour = method, linetype = alpha)) +
geom_line() + facet_grid(d ~ barmu, labeller = label_both) +
xlim(1, xymax) + ylim(0, xymax) +
ylab("Upper bound on the number of false positives") +
xlab(sprintf("Hypotheses sorted by %s", oo))
ggsave(filename = pathname)
}
}
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