R Using CRAN Packages

Step1: Installing R Additional Package from CRAN

To install R additional packages from CRAN, run below command in the SSH terminal (CLI), for tutorial in accessing CLI, please refer to Shell Access and Useful Command

# Load R Environment Module
$ module load R/4.3

# Start R CLI
$ R

# Install Package -> Path:/home/$USER/R
> install.packages(c('<packages to install>'), repos='<repository_url>')

# Install Package (Example)
> install.packages(c('MPsychoR', 'Gifi', 'Cairo'), repos='https://cran.r-project.org')

# Exit R CLI
> quit()

# Purge Module
$ module purge

Step 2: Prepare R Program Source Code

Example source code path -> /home/$USER/job_template/R/MPsychoR_test.R

# Load libraries
library(MPsychoR)
library(Gifi)
library(Cairo)
# Load the built-in dataset
data("zareki")

# Extract subtraction items (columns containing "subtr")
zarsub <- zareki[, grep("subtr", colnames(zareki))]

# Perform nonlinear principal component analysis
prinzar <- princals(zarsub)

# ---------------------------------------------------------
# 1. Export the loadings plot to PNG using Cairo
# ---------------------------------------------------------
CairoPNG(filename = "zareki_subtraction_loadings.png",
    width = 800, height = 600, dpi = 150, bg = "white")

plot(prinzar, main = "Zareki Subtraction Items Loadings Plot")

dev.off()

cat("Loadings plot saved as 'zareki_subtraction_loadings.png'\n in directory:", getwd(), "\n")

# ---------------------------------------------------------
# 2. Export the text results (summary) as a PNG
# ---------------------------------------------------------
# Capture the printed output
output_text <- capture.output(print(prinzar))

CairoPNG(filename = "zareki_subtraction_results.png",
    width = 1000, height = 1400, dpi = 150, bg = "white")

# Create an empty plot and add text
plot.new()
par(mar = c(2, 2, 3, 2))  # Small margins
title(main = "Princals Results: Zareki Subtraction Items",
  cex.main = 1.6, font.main = 2)

# Render the captured text on the canvas
text(x = 0.02, y = 0.98,
  labels = paste(output_text, collapse = "\n"),
  adj = c(0, 1),   # Left- and top-aligned
  cex = 0.85,      # Text size (adjust if needed)
  family = "mono") # Monospace font for clean alignment

dev.off()

cat("Text results saved as 'zareki_subtraction_results.png'\n in directory:", getwd(), "\n")

Step 3: Prepare Job Template Script

Pre-configured template script path -> /home/$USER/job_template/slurm_job/MPsychoR_test.sh

#!/bin/bash
#SBATCH --job-name=MPsychoR_test ## Job Name
#SBATCH --partition=shared_cpu ## Partition for Running Job
#SBATCH --nodes=1 ## Number of Compute Node
#SBATCH --ntasks-per-node=1 # Number of Task per Compute Node
#SBATCH --cpus-per-task=2 ## Number of CPU per task
#SBATCH --time=60:00 ## Job Time Limit (i.e. 60 Minutes)
#SBATCH --mem=10GB ## Total Memory for Job
#SBATCH --output=./%x%j.out ## Output File Path
#SBATCH --error=./%x%j.err ## Error Log Path

## Initiate Environment Module
source /usr/share/modules/init/profile.sh

## Reset the Environment Module components
module purge

## Load Module
module load R/4.3

## Run user command
Rscript /home/${USER}/job_template/R/MPsychoR_test.R

## Clear Environment Module components
module purge

Step 4: Create Template (Web Interface Feature)

To submit HPC via web interface a job template is required, details please refer to: HPC Job Template For Job submission via CLI Terminal, please skip this step.

Step 5: Submit HPC Job

Guides for submitting HPC job, please refer to: HPC Job Submission

Step 6: Reset user’s R Environment (Optional)

# Reset User’s R Environment
$ rm -rf /home/$USER/R