CPU Time
In the following, time, as a function of network size, is investigated for several cores compared to NCT. Note that all settings in GGMncv are set to be comparable to NCT, for example, using lasso and the number of tuning parameters (i.e., 50). One important distinction is that GGMncv compute 4 default test-statistic instead of 2 (as in NCT).
library(GGMncv)
library(dplyr)
library(ggplot2)
library(NetworkComparisonTest)
p <- seq(10, 25, 5)
sim_fun <- function(x){
main <- gen_net(p = x, edge_prob = 0.1)
y1 <- MASS::mvrnorm(n = 500,
mu = rep(0, x),
Sigma = main$cors)
y2 <- MASS::mvrnorm(n = 500,
mu = rep(0, x),
Sigma = main$cors)
st_1 <- system.time({
fit_1 <- nct(Y_g1 = y1,
Y_g2 = y2,
iter = 1000,
desparsify = FALSE,
penalty = "lasso",
cores = 1,
progress = FALSE)
})
st_2 <- system.time({
fit_1 <- nct(Y_g1 = y1,
Y_g2 = y2,
iter = 1000,
desparsify = FALSE,
penalty = "lasso",
cores = 2,
progress = FALSE)
})
st_4 <- system.time({
fit_1 <- nct(Y_g1 = y1,
Y_g2 = y2,
iter = 1000,
desparsify = FALSE,
penalty = "lasso",
cores = 4,
progress = FALSE)
})
st_8 <- system.time({
fit_1 <- nct(Y_g1 = y1,
Y_g2 = y2,
iter = 1000,
desparsify = FALSE,
penalty = "lasso",
cores = 8,
progress = FALSE)
})
st_NCT <- system.time({
fit_NCT <- NCT(data1 = y1,
data2 = y2,
it = 1000,
progressbar = FALSE)
})
ret <- data.frame(
times = c(st_1[3], st_2[3],
st_4[3], st_8[3], st_NCT[3]),
models = c("one", "two",
"four", "eight", "NCT"),
nodes = x
)
return(ret)
}
sim_res <- list()
reps <- 5
for(i in seq_along(p)){
print(paste("nodes", p[i]))
sim_res[[i]] <- do.call(rbind.data.frame,
replicate(reps, sim_fun(p[i]),
simplify = FALSE))
}
do.call(rbind.data.frame, sim_res) %>%
group_by(models, nodes) %>%
summarise(mu = mean(times),
std = sd(times)) %>%
ggplot(aes(x = nodes, y = mu, group = models)) +
theme_bw() +
geom_ribbon(aes(ymax = mu + std, ymin = mu - std),
alpha = 0.1) +
geom_line(aes(color = models), size = 2) +
ylab("Seconds") +
xlab("Nodes") +
scale_color_discrete(name = "Model",
labels = c("GGMncv(8)",
"GGMncv(4)",
"GGMncv(2)",
"GGMncv(1)",
"NCT"),
breaks = c("eight",
"four",
"two",
"one",
"NCT"))
The performance gains are clear, especially when using 8 cores with GGMncv.