107 lines
3.2 KiB
R
107 lines
3.2 KiB
R
# -----------------------------------------------------------------------------
|
|
# Program: runtime_test.R
|
|
# Author: Loki
|
|
# Date: 2019.08.12
|
|
#
|
|
# Purpose:
|
|
# Comparing runtime of "MAVE" with "CVE".
|
|
#
|
|
# RevisionHistory:
|
|
# Loki -- 2019.08.12 initial creation
|
|
# -----------------------------------------------------------------------------
|
|
|
|
# load CVE package
|
|
library(CVE)
|
|
# load MAVE package for comparison
|
|
library(MAVE)
|
|
|
|
# set nr of simulations per dataset
|
|
nr.sim <- 10
|
|
|
|
# set names of datasets to run tests on
|
|
dataset.names <- c("M1", "M2", "M3", "M4", "M5")
|
|
|
|
#' Orthogonal projection to sub-space spanned by `B`
|
|
#'
|
|
#' @param B Matrix
|
|
#' @return Orthogonal Projection Matrix
|
|
proj <- function(B) {
|
|
B %*% solve(t(B) %*% B) %*% t(B)
|
|
}
|
|
|
|
#' Compute nObs given dataset dimension \code{n}.
|
|
#'
|
|
#' @param n Number of samples
|
|
#' @return Numeric estimate of \code{nObs}
|
|
nObs <- function (n) { n^0.5 }
|
|
|
|
## prepare "logging"
|
|
# result error, time, ... data.frame's
|
|
error <- matrix(nrow = nr.sim, ncol = 2 * length(dataset.names))
|
|
time <- matrix(nrow = nr.sim, ncol = 2 * length(dataset.names))
|
|
# convert to data.frames
|
|
error <- as.data.frame(error)
|
|
time <- as.data.frame(time)
|
|
# set names
|
|
names(error) <- kronecker(c("CVE.", "MAVE."), dataset.names, paste0)
|
|
names(time) <- kronecker(c("CVE.", "MAVE."), dataset.names, paste0)
|
|
|
|
# get current time
|
|
start.time <- Sys.time()
|
|
## main comparison loop (iterate `nr.sim` times for each dataset)
|
|
for (i in seq_along(dataset.names)) {
|
|
for (j in 1:nr.sim) {
|
|
name <- dataset.names[i]
|
|
# reporting progress
|
|
cat("\rRunning Test (", name, j , "):",
|
|
(i - 1) * nr.sim + j, "/", length(dataset.names) * nr.sim,
|
|
" - Time since start:", format(Sys.time() - start.time), "\033[K")
|
|
# sample new dataset
|
|
ds <- dataset(name)
|
|
k <- ncol(ds$B) # real dim
|
|
data <- data.frame(X = ds$X, Y = ds$Y)
|
|
# call CVE
|
|
cve.time <- system.time(
|
|
cve.res <- cve(Y ~ .,
|
|
data = data,
|
|
method = "simple",
|
|
k = k)
|
|
)
|
|
# call MAVE
|
|
mave.time <- system.time(
|
|
mave.res <- mave(Y ~ .,
|
|
data = data,
|
|
method = "meanMAVE")
|
|
)
|
|
# compute real and approximated sub-space projections
|
|
P <- proj(ds$B) # real
|
|
P.cve <- proj(cve.res$B)
|
|
P.mave <- proj(mave.res$dir[[k]])
|
|
# compute (and store) errors
|
|
error[j, paste0("CVE.", name)] <- norm(P - P.cve, 'F') / sqrt(2 * k)
|
|
error[j, paste0("MAVE.", name)] <- norm(P - P.mave, 'F') / sqrt(2 * k)
|
|
# store run-times
|
|
time[j, paste0("CVE.", name)] <- cve.time["elapsed"]
|
|
time[j, paste0("MAVE.", name)] <- mave.time["elapsed"]
|
|
}
|
|
}
|
|
|
|
cat("\n\n## Time [sec] Means:\n")
|
|
print(colMeans(time))
|
|
cat("\n## Error Means:\n")
|
|
print(colMeans(error))
|
|
|
|
len <- length(dataset.names)
|
|
boxplot(as.matrix(error),
|
|
main = paste0("Error (nr.sim = ", nr.sim, ")"),
|
|
ylab = expression(error == group("||", P[B] - P[hat(B)], "||")[F] / sqrt(2*k)),
|
|
las = 2,
|
|
at = c(1:len, 1:len + len + 1)
|
|
)
|
|
boxplot(as.matrix(time),
|
|
main = paste0("Time (nr.sim = ", nr.sim, ")"),
|
|
ylab = "time [sec]",
|
|
las = 2,
|
|
at = c(1:len, 1:len + len + 1)
|
|
)
|