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CVE/runtime_test.R

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# Usage:
# ~$ Rscript runtime_test.R
#' Writes log information to console. (to not get bored^^)
tell.user <- function(name, start.time, i, length) {
cat("\rRunning Test (", name, "):",
i, "/", length,
" - elapsed:", format(Sys.time() - start.time), "\033[K")
}
library(CVE) # load CVE
source("CVE_legacy/function_script.R") # Source legacy code
# Number of simulations
SIM.NR <- 50
# maximal number of iterations in curvilinear search algorithm
MAXIT <- 50
# number of arbitrary starting values for curvilinear optimization
ATTEMPTS <- 10
# set names of datasets
dataset.names <- c("M1", "M2", "M3", "M4", "M5")
# Set used CVE method
# methods <- c("legacy", "simple", "sgd")
methods <- c("legacy", "simple", "sgd")
# Setup error and time tracking variables
error <- matrix(NA, SIM.NR, length(methods) * length(dataset.names))
time <- matrix(NA, SIM.NR, ncol(error))
colnames(error) <- kronecker(paste0(dataset.names, '-'), methods, paste0)
colnames(time) <- colnames(error)
# Create new log file and write CSV (actualy TSV) header.
# (do not overwrite existing logs)
log.nr <- length(list.files('tmp/', pattern = '.*\\.log'))
file <- file.path('tmp', paste0('test', log.nr, '.log'))
cat('dataset\tmethod\terror\ttime\n', sep = '', file = file)
# Open a new pdf device for plotting into (do not overwrite existing ones)
pdf(file.path('tmp', paste0('test', log.nr, '.pdf')))
# only for telling user (to stdout)
count <- 0
start.time <- Sys.time()
# Start simulation loop.
for (sim in 1:SIM.NR) {
# Repeat for each dataset.
for (name in dataset.names) {
count <- count + 1
tell.user(name, start.time, count, SIM.NR * length(dataset.names))
# Create a new dataset
ds <- dataset(name)
# Prepare X, Y and combine to data matrix
Y <- ds$Y
X <- ds$X
data <- cbind(Y, X)
# get dimensions
dim <- ncol(X)
truedim <- ncol(ds$B)
for (method in methods) {
if (tolower(method) == "legacy") {
dr.time <- system.time(
dr <- stiefl_opt(data,
k = dim - truedim,
k0 = ATTEMPTS,
h = estimate.bandwidth(X, k = truedim, nObs = sqrt(nrow(X))),
maxit = MAXIT
)
)
dr$B <- fill_base(dr$est_base)[, 1:truedim]
} else {
dr.time <- system.time(
dr <- cve.call(X, Y,
method = method,
k = truedim,
attempts = ATTEMPTS
)
)
}
key <- paste0(name, '-', method)
error[sim, key] <- subspace_dist(dr$B, ds$B) / sqrt(2 * truedim)
time[sim, key] <- dr.time["elapsed"]
# Log results to file (mostly for long running simulations)
cat(paste0(
c(name, method, error[sim, key], time[sim, key]),
collapse = '\t'
), '\n',
sep = '', file = file, append = TRUE
)
}
}
}
cat("\n\n## Time [sec] Means:\n")
print(colMeans(time))
cat("\n## Error Means:\n")
print(colMeans(error))
at <- seq(ncol(error)) + rep(seq(ncol(error) / length(methods)) - 1, each = length(methods))
boxplot(error,
main = paste0("Error (Nr of simulations ", SIM.NR, ")"),
ylab = "Error",
las = 2,
at = at
)
boxplot(time,
main = paste0("Time (Nr of simulations ", SIM.NR, ")"),
ylab = "Time [sec]",
las = 2,
at = at
)